Steal like a(n Open) Scientist

Science is give and take

“After giving talks about open science I’ve sometimes been approached by skeptics who say, ‘Why would I help out my competitors by sharing ideas and data on these new websites? Isn’t that just inviting other people to steal my data, or to scoop me? Only someone naive could think this will ever be widespread.’ As things currently stand, there’s a lot of truth to this point of view. But it’s also important to understand its limits. What these skeptics forget is that they already freely share their ideas and discoveries, whenever they publish papers describing their own scientific work. They’re so stuck inside the citation-measurement-reward system for papers that they view it as a natural law, and forget that it’s socially constructed. It’s an agreement. And because it’s a social agreement, that agreement can be changed. All that’s needed for open science to succeed is for the sharing of scientific knowledge in new media to carry the same kind of cachet that papers do today” (Nielson 2011).

[T]he work of culture more generally may be seen as training towards letting (things) go. If culture is all about conveying things and skills to others…then learning to let go of things that others appropriately demand is a permanent process. Just as those from whom I have received skills and knowledge (and positions and objects and my life) had to let go of their possessions in the course of their lives, so will I have to learn to let go…” (Widlok 2016).

PLEASE NOTE: This is a draft of a bit of the Open Scientist Handbook. There are references/links to other parts of this work-in-progress that do not link here in this blog. Sorry. But you can also see what the Handbook will be offering soon. All comments are helpful!

In his book Steal like an Artist, Auston Kleon (2012) reminds artists that their lives have been surrounded by art, and that their “original” ideas have been informed in myriad ways by their exposure to this. Stealing is unavoidable, so do it right. Additionally, new art (including music) is always positioned inside of and/or away from the art preceding this. There is an abundance of influences to use, and a debt to all of them. Be bold and remix what you find, celebrate the old ideas in your new work. Don’t simply copy something and call it yours, but do study and learn from any source worth stealing. Investigate the meanings and potentials of what you find, and then transform these from those insights born of your personal onlyness (See: The Onlyness of the Career Open Scientist). Science is an art, with a similar relationship to its ideas. So your job is to learn how to steal like a scientist.

You are a scientist. You’re not agent 007. You are really more like agent C20H25N3O. But you do have a license. A license to steal. Come closer. Be honest. You are always on the lookout for ideas worth stealing. If the journal article you’re reading is not worth stealing, toss it away and keep looking. You are always looking. It’s called “research.” You hope your own team’s ideas are worth stealing. You make stealing these easy. It’s called “publication.” You are a professional thief. You keep careful track of the ideas you steal. You know where they are from. You’ve read the articles, you’ve read the articles they cited. You’ve read the articles from the citations in those articles. Life would be a lot easier if you could just spin up new ideas on your own. Science doesn’t work that way.

“We may consider sharing to be tolerated scrounging but for the scrounging to be tolerated it has to build on a number of recognized modes of action and interaction” (Widlok 2013).

“Saul Bellow, writing to a friend … said: ‘The name of the game is Give All. You are welcome to all my facts. You know them, I give them to you. If you have the strength to pick them up, take them with my blessing’” (Lethem 2007; Accessed July 20, 2020).

Stealing like a scientist in the open-science economy means you get to ask for and take what you need, in culturally specific ways. You take resources to use and reuse, to mine and remix. You pull knowledge from these, and add insights to them in the process. In hunter-gatherer societies (and sometimes in college dormitories), this is called “tolerated scrounging.” In the academy it’s more like “celebrated reuse.” Open-science research repositories make reuse quick and easy, and they are filled with ideas worth stealing. And, since these are “non-rivalrous” (See: Neylon 2016), an unlimited number of scientists can steal them. Better still, the more these ideas are stolen, the greater their value.

The culturally specific rules for stealing are being fashioned through the governance processes of scholarly commons (See: scholarly commons), as these are created to steward common pooled resources toward optimal use. The removal of patents for basic research (See: Hyde 2009; Barnett 2020), is one starting point. Fully public open-access publishing is another. Start somewhere and grow a culture of tolerated scrounging for the resources in your scholarly commons.

The responsibility is yours, the credit belongs to the whole scholarly club

[R]esearchers saw maintaining responsible conduct as the mandatory responsibility of every individual scientist. By choosing this card, the discussants assumed that science’s most important responsibility to society was to produce reliable knowledge. Research misconduct is then seen as the main threat to this practice…” (Sigl et al 2020).

When you gift (publish) a new scholarly work, you shoulder every responsibility for the rigor in your methods and any issues with your data. This is the first of several social responsibilities (such as mentoring others) you always carry, and one of the keystone virtues the academy has demanded for hundreds of years. Still, you are not the first nor the final author of your own findings. That authority is attached to a thousand places in the prior ideas of others, and in the work of more scientists yet to happen. You merely added one piece to an ongoing solution to the puzzle of nature (or society, etc.): to the “one long experiment” (Martin 1998) that is science. Time to get humble; but if intellectual humility doesn’t sound like you, you can claim hypo-egoic nonentitlement (Banker and Leary 2019) instead.

You own the event of discovery, not the piece of knowledge that was produced

Stealing like a scientist in an open gift economy also means everyone else gets to steal from you. When they steal like scientists, this makes you happy. It means your works are steal-worthy. You celebrate their reuse. In fact you need others to reuse your work to show its reproducibility. Your claim is that anyone would necessarily arrive at the very same insight you had, proving that this insight has a durable purchase on its object. If nobody can or does reuse your work, its value is unknown and even suspect.

What is harder to admit is the amount of luck, the confluence of good fortune that brought you to the event where you and your team acquired some new insight. Nobody gets to own serendipity. “Serendipity is a category used to describe discoveries that occur at the intersection of chance and wisdom” (Copeland 2019).

Riding on the back of the serendipity of reading what you did, talking with whom you have, and trying something new, you’ve exercised rigor and wonder and perseverance enough through your research to find that one distinct piece of the puzzle to apply it exactly where it fits. Now, you are expected to honor and celebrate the many contemporary and prior ideas that helped you and your team arrive at the singular event within which this new insight was born (See: Shaming the giant). By this, you also show that you belong to the elite club of science. And those who steal your ideas will honor and celebrate them in theirs.

Who can steal a gift? The expected answer is: nobody. The correct answer is: everyone.

As an open scientist, you have four jobs:

1.) produce ideas worth stealing, and;

2.) make these ideas as easy to steal as possible;

3.) steal as much from other scientists as you need, but steal like a scientist;

4.) become an active maintainer in your commons, to keep the stealing opportunities rich and rewarding for everyone.

As a member of a scholarly commons, you also have the duty to create normative cultural practices to optimize stealing going forward. Your list of “good stealing” practices will be fashioned to meet the needs of all the commoners in your community. Here’s a sample list:

Scientists know the difference

The Good Stealing practices involve care and attention to the provenance of what’s being stolen, and active credit for those who have made stealing possible. The Bad Stealing practices all point to a game of personal gain based on hiding the sources of your own learning. Good Stealing understands that stewarding the abundance of open resources is a long-term — longer than any lifetime — practice. Today, Bad Stealing practices — the hoarding, scooping, credit-grabbing kinds that are supported by the invented scarcity of ideas and the diminished value for generosity in science — flourish in the absence of social attention and alternative cultural norms. Tomorrow, when open science defines the norms for sharing, gifting, and celebrated reuse, Bad Stealing can be banished to the social margins, and ridiculed as needed.

Tolerated scrounging takes time and effort

On disinterestedness and serendipity: the freedom to discover and share in (open) science

“Disinterestedness: Scientists are motivated by the desire for knowledge and discovery, and not by the possibility of personal gain.
Self-Interestedness: Scientists compete with others in the same field for funding and recognition of their achievements” (Anderson, et al. 2007).

Let’s dig a little deeper into “celebrated reuse” and the history of science. The Mertonian norms of science include a notion of “disinterestedness.” At the time Merton was writing, this norm announced a basic freedom to pursue science without conflicts of interests, to shield basic science research from the motivations and (perverse) incentives that come with the marketplace, say, or with other external social/political/military desires. As Vannevar Bush (Accessed August 1, 2020) noted: “Scientific progress on a broad front results from the free play of free intellects, working on subjects of their own choice, in the manner dictated by their curiosity for exploration of the unknown.” Disinterestedness is also the culturally valued attitude of “letting go” when others build on your findings.

Disinterestedness was, and still is, the classic norm that frees you to let others in the academy club steal your work. The same lack of self interest that validates your independent research choice also validates you being able to let other people freely use your work. Disinterestedness is one of the social costs of academic freedom (you probably can’t have one without the other). It is the reason why the imbalance between responsibility (you have 100% of this) and authority (you have very little of this) makes perfect sense. You take the freedom to choose your research path in exchange for gifting the results back to the community; you release your personal interest in these results to benefit the whole scientific club.

If self-interest is your main incentive to do science, you are not doing open-science. Worse than that, you are doing science wrong. If you decide to wait until you have tenure to throw off self-interest (Anderson et al 2010), you are also doing it wrong. Certainly, we all have a stake in our own interests. Science expects us to care for these interests outside of our scientific explorations, and we need institutional reform and support to get there. But mainly, disinterestedness tells us to avoid conflicts with interests from outside the “republic of science” (Polanyi 1962).

Kindness and care still matter

“[M]uch of academic thinking brackets issues of emotions and values outside of academic understanding, even though emotions and values inhabit research and teaching by virtue of what we know, what we choose not to know, what we prioritise and what we trivialise” (Lynch and Ivancheva 2016).

Disinterestedness — that freedom to choose your own research subject and become passionate about exploring this — is not an alibi to ignore/resist other organizational cultural values for the academy, values that include kindness and care in academy workplaces and in relations with colleagues. (See: Kindness and care) You can start by bracketing out the perverse marketplace incentives that might warp your research path and diminish your own passion for the pursuit of science.

Passion is another part of science that is not peculiar to you. You are not the only person in the room or on your team that has been infected with the intellectual disease of science. This is a long-term global knowledge pandemic. Everyone gets to be infected — to be passionate — in their own way. (See: Six rules about passion). Exploring these passions through years of rigorous research effort builds a kind of shared practical wisdom inside the profession.

Applied practical wisdom: the practice of open science

The practical wisdom that underpins actually doing science removes the need for other incentives. The answer to the question: “How do you incentivize scientists to do research and teaching?” is simply this: “give them more opportunities to learn the practical wisdom required to do science” (See: The practical wisdom of science praxis).

Science requires/rewards its own unique practical wisdom. In addition to the practical wisdom one might (and perhaps should) acquire through social experiences with others (colleagues, family, strangers), doing science offers opportunities to acquire practical wisdom through a career experiencing nature as a complex emergent system.

For many years you learned from (and stole from) your teachers. Now, you encourage your students to scrounge new knowledge. Today, you steal like a scientist: information from your objects of study and insights from conversations with your colleagues. In tomorrow’s open-science culture, culturally-informed practices of Good Stealing will help you and your team and your organization optimize the use of the emergent scholarly commons infrastructure and content.

The work needed to articulate and support these practices will be significant. But know that the work needed to articulate and support Bad Stealing is/was just as arduous, except that so many academics have already learned how. Unlearning these toxic cultural practices will take time and reflection. Today, dozens of open-science platforms and communities are encouraging effective reuse. Reuse is one metric that deserves to become a goal (and one goal that makes a handy metric). How does your organization, your discipline, or your team celebrate active reuse? Where can it improve?

References

Anderson, Melissa S, Emily A. Ronning, Raymond De Vries, and Brian C. Martinson. “Extending the Mertonian Norms: Scientists’ Subscription to Norms of Research.” The Journal of Higher Education 81, no. 3 (2010): 366–93. https://doi.org/10.1353/jhe.0.0095.

Anderson, Melissa S., Brian C. Martinson, and Raymond De Vries. “Normative Dissonance in Science: Results from a National Survey of U.S. Scientists.” Journal of Empirical Research on Human Research Ethics 2, no. 4 (December 2007): 3–14. https://doi.org/10.1525/jer.2007.2.4.3.

Banker, Chloe C, and Mark R Leary. “Hypo-Egoic Nonentitlement as a Feature of Humility.” Personality and Social Psychology Bulletin, 2019, 0146167219875144.

Copeland, Samantha. “On Serendipity in Science: Discovery at the Intersection of Chance and Wisdom.” Synthese 196, no. 6 (June 2019): 2385–2406. https://doi.org/10.1007/s11229-017-1544-3.

Hyde, Lewis. The Gift: Creativity and the Artist in the Modern World. Vintage, 2009.

Kleon, Austin. Steal like an Artist: 10 Things Nobody Told You about Being Creative. New York: Workman Pub. Co, 2012.

Lynch, K, and M Ivancheva. “Academic Freedom and the Commercialisation of Universities: A Critical Ethical Analysis.” Ethics in Science and Environmental Politics 15, no. 1 (March 31, 2016): 71–85. https://doi.org/10.3354/esep00160.

Martin, Ronald E. One Long Experiment: Scale and Process in Earth History. Columbia University Press, 1998.

Nielsen, M. Reinventing Discovery: The New Era of Networked Science. Princeton University Press, 2011.

Polanyi, M. “The Republic of Science: Its Political and Economic Theory.” Minerva 1 (1962): 54–73.

Sigl, Lisa, Ulrike Felt, and Maximilian Fochler. “‘I Am Primarily Paid for Publishing…’: The Narrative Framing of Societal Responsibilities in Academic Life Science Research.” Science and Engineering Ethics 26, no. 3 (June 2020): 1569–93. https://doi.org/10.1007/s11948-020-00191-8.

Widlok, T. Anthropology and the Economy of Sharing. Routledge, 2016.

— — — . “Sharing: Allowing Others to Take What Is Valued.” HAU: Journal of Ethnographic Theory 3, no. 2 (2013): 11–31.

Time for the academy to retire the giants

The academy can’t afford a culture centered on creating giants in their fields

“If I have seen further it is by standing on the sholders [sic] of Giants.” Isaac Newton. 1676. Letter to Robert Hooke (before they became bitter enemies). This notion was a commonplace in the 17th Century, with the implications that even a dwarf would see further than a giant if he were standing on the giant’s shoulders. (Wikipedia).

“If our team’s ideas add value to the current state of knowledge, it is because we have stolen widely and well from the abundance of prior understanding surrounding us, and climbed a stairway of knowledge built by others.” Modern version… no giants.

PLEASE NOTE: This is a draft of a bit of the Open Scientist Handbook. There are references/links to other parts of this work-in-progress that do not link here in this blog. Sorry. But you can also see what the Handbook will be offering soon.

Open science needs to admit that no scientist is a lone giant in their field

One of the hard lessons for open science is to abandon the notion that “great” scientists — those “giants” of the academy — were and are individuals of some unique and rare quality; that their shoulders tower above those of their peers, and that the optimal career goal of a scientist is to become a giant in their field. And, if you are a woman in science, while standing on the shoulders of “giants” in the academy, you can be fairly certain that some of them would have been intent on looking up your skirt; another reason why open science needs Fierce Equality.

In Isaac Newton, the Asshole who Reinvented the Universe (Freistetter 2018) we get a picture of Newton’s brilliance as a natural philosopher, and of his serial acts of intellectual and careerist selfishness. Biographies of Newton’s career and personality issues are several (See also: Clark and Clark 2001; Manuel 1979; Gleick 2004). The biographies of several of his contemporaries (Leibniz, Hooke, Gray, and Flamsteed for starters) reveal their side of the dangers of being on Newton’s wrong side. But then Newton’s bad behavior was not as unusual as it perhaps should have been. Rather, it was distinguished by its obsessive persistence, and made potent by Newton’s position at the head of the Royal Society. Freistetter excused much of Newton’s bad behavior as emblematic of an academy culture where intellection was — and still is — a cerebral variety of blood sport. He did venture that Newton would still be called an asshole if he were working today.

Newton’s interpersonal misconduct is less of an issue here. For more on assholes, take a look at The Need for a Zero-Asshole Zone. While producing a series of astonishing research findings from his own work, Newton was soaking up ideas and credit from others, while insisting that his ideas were his alone. Apparently, we wasn’t entirely serious about the whole “giants’ shoulders” thing.

You want to get good at doing science — as a personal goal — because this leads to more satisfaction in your daily life and career, and because you can become more valuable to science by having better conversations that lead to more interesting questions and new ideas. Your getting better at being a scientist should, in no manner obstruct others on their path to getting better at this. In fact, one of the advantages of open work in science is that you can lift others during your climb up the same stairs. You can always grow. You can grow a larger sense of the science you are working with/on, a perception of how your work fits into the field, and appreciation for the work of your colleagues. Your primary challenge is to be better at science (and being human) today than you were yesterday.

A lot of scientists worked to build the stairs you are climbing

“[B]y some measure, every important innovation is fundamentally a network affair” (Johnson 2011).

“[M]odern scholarship is based on cooperation. Ideas are not created in a vacuum. Reuse of research processes, methods and results as well as abstraction and extension should therefore represent basic values of scholarly communication. The possibility to reuse data, materials and results enables researchers and communities to learn from each other and to speed up the production of new knowledge” (Vienna Principles 2016; Accessed July 10, 2020).

There’s a badge for that

What’s wrong with having and celebrating “giants” in your field? We can explore this. Firstly, the goal of exclusive achievement and individual fame requires and produces way too much scarcity in the process (Against Exclusion: open is open to all). In the game of “giant-making,” recognition points might need to be hoarded, reputation metrics jealously guarded, and ideas (and data) locked away until some strategic moment. Secondly, the practice of acknowledging a science giant requires the production of science dwarves. It’s a zero-sum game. If nobody’s small, someone can’t be giant. Most giants only look large from far away because of the cumulative advantages they were given across their careers. They are actually standing on the shoulders of privilege. Finally, the desire to be a giant fuels narcissistic behavior, of which the academy has an abundance already.

“As Justice Louis Brandeis, who witnessed our previous Gilded Age, might have said: ‘We may have democracy, or we may have praise showered on the heads of a few, but we can’t have both’” (Johnson 2019: Accessed July 24, 2020)

In a fiercely-equal, open-science culture, zero-sum games of prizes and awards handed out to would-be giants can be replaced in favor of a larger emphasis on a system of open badges that anyone can earn: with intention, time, and effort (An Introduction to Badges). The use of badges earned instead of prizes won for recognition of accomplishments would build a reputation economy for the academy that rewards achievement anywhere on the planet, and refocusses attention on science’s generative engine: learning and community effort. “Although the edifice of scientific understanding is sometimes envisaged as an accumulation of individual discoveries, in reality science is a community effort comprising innumerable interdependent contributions. Credit is disproportionately awarded to principal investigators for what is truly the product of teamwork, and nearly all scientific contributions are heavily dependent on knowledge obtained earlier…. In the spirit of an Amish barn-raising, a celebration of the collective achievement of science should subsume individual achievement” (Casadevall and Fang 2012 [ASM]).

The finite game (Open Science and the Infinite Game) of “making a name for oneself” in the academy is far too expensive to the academy to allow this to be a central goal of science. Science demands so much already from you: both rigor and wonder, and in generous amounts. “Science is an inherent contradiction — systematic wonder — applied to the natural world” (Lewis et al. 2001).

Because it is important to regularly celebrate open science cultural practices, and contributions to science, and to institutions, and teams, you can create honors that are playful and honest (Celebrate Open Science). Science doesn’t need fellows in national academies as much as it needs researchers who deserve to get honored for their dedication and their kindness. Be generous to those who are, too. Don’t tell your team members to “leave their frowns at home,” but hand out medals (perhaps made of chocolate) to those with the most difficulties to overcome, and the best spirit. Give away prizes every week. Cheer when someone earns a difficult badge. Turn learned society elections into lotteries, and celebrate when volunteer leaders chosen at random step up and perform. Find ways to reward as many early career colleagues as possible. In the end, you realize that everyone who makes a serious attempt to do science is already a giant. You didn’t notice because you are one too.

Marc McGinnes taught for decades at UCSB. On civic holidays, he would walk on stilts as an “occasional giant.” He is a giant in many ways.

Afterthoughts: If you still want to be a giant, be a giant for your family, be a giant in your town. Perhaps there used to be giants, back when the only way to fund science was to attract the attention and the purse of a king. If the person paying your rent is named de’ Medici, perhaps you should get used to wearing stilts, just ask Galileo Galilei. The main lesson of that famous “standing on the sholders of giants” quote is that if you are going to be a life-long jerk, pop some really nice sentiments on your blog that people might remember you by three hundred years later. Even then, someone will write a book about what an asshole you were.

References

Casadevall, Arturo, and Ferric C Fang. Reforming Science: Methodological and Cultural Reforms. Am Soc Microbiol, 2012.

Clark, David H., and Stephen P. H. Clark. Newton’s Tyranny: The Suppressed Scientific Discoveries of Stephen Gray and John Flamsteed. New York: W.H. Freeman and Co, 2001.

Freistetter, F. Isaac Newton: The Asshole Who Reinvented the Universe. First American hardcover edition in English. Amherst, New York: Prometheus Books, 2018.

Gleick, James. Isaac Newton. New York; Westminster: Vintage Imprint ; Knopf Doubleday Publishing Group ; Random House, Incorporated Distributor, 2004. http://site.ebrary.com/id/10063736.

Johnson, S. Where Good Ideas Come from: The Seven Patterns of Innovation. Penguin UK, 2011.

Lewis, Thomas, Fari Amini, and Richard Lannon. A General Theory of Love. 1. Vintage ed. New York: Vintage, 2001.

Manuel, Frank Edward. A Portrait of Isaac Newton. Washington: New Republic Books, 1979.

The dance of demand-sharing culture in open science

Working together in time. Open science culture promotes active belonging in the community of science [photo: Nick Ansell CC license in Flickr]

“I am not saying science is a community that treats ideas as contributions; I am saying it becomes one to the degree that ideas move as gifts” (Hyde, 2009).

“The specificity of [demand] sharing… is rather that it also constitutes sharing in, granting access to the flows of objects, their intrinsic goods, and their intrinsic value” (Widlok, 2013).”

“That is the fundamental nature of gifts: they move, and their value increases with their passage. The fields made a gift of berries to us and we made a gift of them to our father. The more something is shared, the greater its value becomes. This is hard to grasp for societies steeped in notions of private property, where others are, by definition, excluded from sharing” (Kimmerer, 2013).

PLEASE NOTE: This is a draft of a bit of the Open Scientist Handbook. There are references/links to other parts of this work-in-progress that do not link here in this blog. Sorry. But you can also see what the Handbook will be offering soon.

So, you will want to change the culture of your organization to enable “demand sharing” (See: Demand Sharing). This is something the Handbook encourages, and, after reading this section, you will understand why. The goal of this culture change is to build an internal economy for the scholarly resources you are now assembling. This economy will do two somewhat intertwined things:

1. optimize the value of these resources, and;

2. support their use through practices that respect and enable fierce equality (See: Fierce Equality) across the global “republic of science” and beyond.

The argument here is that the current, scarcity-based market economy that has penetrated inside the academy does neither of these things well enough, and sometimes not at all. What the market economy does do is capture external motivations that appear to power efficient use. Instead, these motivations infest the academy with unavoidable conflicts of interest and perverse incentives. This form of economy ends up externalizing much of the value of research goods. These become properties held outside of the academy — from which they were born; this happens today, every time you gift Elsevier or Wiley the copyright to your research article. While this arrangement frees the academy from investing in the repositories that could hold these goods internally, and in recognition schemes to highlight great work and show gratitude to science teams doing this work, the cost is significant and ongoing: the academy needs to pay over and over again to access its own resources.

The cultural practices that support demand sharing are not simple at all. Not nearly as simple as the market transactions we do every day. They require active, culturally coded, shared intentions. Think of them as a learned, shared cultural “choreography.” Every member of the group knows how to dance with the group. These practices are durable enough to have sustained hunter-gatherer groups across the planet for tens of thousands of years, sophisticated enough to enable entire small societies to manage almost all of their internal transactions, and logical and transparent enough so that children do learn and follow them.

“Almost everyone [in the social sciences] continues to assume that in its fundamental nature, social life is based on the principle of reciprocity, and therefore that all human interaction can best be understood as a kind of exchange…
…Exchange is all about equivalence. It’s a back-and-forth process involving two sides in which each side gives as good as it gets” (Graeber, 2011).

Reciprocity and gift economies unpacked

Let’s look closer at socio/anthropological notions of a “gift economy” and “reciprocity,” and more recent work in economic history and economic anthropology for new insights to the “sharing economy.” In anthropology, reciprocity is a topic that has launched a thousand dissertations, that has informed entire schools of theory and argument, and that has been the wellspring of anthropology’s connection to economics since Marcel Mauss’s book, The Gift, was published in French in 1925.

The Handbook assumes your goal here, or one of them, is to avoid needing to become an anthropologist in order to be a culture-change agent. Here are the basics of gift economies and reciprocity you might call upon without further study.

Let’s start with the conclusion: demand-sharing is a form of reciprocity that requires active, intentional cultural practices to deliver an optimal return for the academy. Demand sharing is a practical/theoretical upgrade on the notion of the academy as a “gift economy.” It describes a relationship in practice between scientists and science, between scholars and the academy.

Start with reciprocity

At its core this is a durable obligation to interact with others. So, this behavior is culturally coded (more about this later). Inside the community, exchanges get made that motivate future exchanges. Importantly, these obligations are never designed to achieve a final closure. Reciprocity in life and in the academy is a feature of an infinite game. Reciprocity colonizes your future by enrolling you in longitudinal practices of giving and getting. When your child finishes college, you do not present them with a bill for all of the expenses they cost you growing up. If you do, you are planning to never see them again.

Market transactions (and also theft) avoid this type of ongoing obligation. So does charity, mostly. When you sell your old car to a stranger for cash, you have every hope that you will never see them again. When a thief breaks into your office and takes a computer, you do not expect them to give you something back in the future. When you give some food to a homeless person on the street, you don’t expect to get something material back from them later on.

Reciprocity takes more work (cultural and emotional) to maintain than direct market exchanges. It takes a shared understanding of the implied obligations for reciprocity to succeed as an economic logic. For this reason, reciprocity works best inside a community. Transactions between different communities involve more rule-making, and less cultural coding. Considering the academy as a community, or a collection of like-minded communities, some form of reciprocity is an economic logic that fits very well, once the cultural practices for this become normative.

In some cases, the implied obligations of reciprocity can negatively color the relationships between individuals: “When favors come with strings attached or implied, the interaction can leave a bad taste, feeling more like a transaction than part of a meaningful relationship. Do you really care about helping me, or are you just trying to create quid pro quo so that you can ask for a favor?” (Grant 2013).

Reciprocity can be generalized or more specific, and both forms can be active in the same culture. “Generalised reciprocity is characterised by Marshall Sahlins as being marked by a weak obligation to reciprocate and an indifference to the time, quality or quantity of the return. It is typically the behaviour found between such closely related people as parents and children or siblings, where asking for things is widely acceptable…” (Peterson, 1993). Generalized reciprocity brings in a key feature of demand-sharing: the right to ask for what you need. You can say that demand-sharing is a certain specific type of generalized reciprocity, highly coded to be efficient and sufficient across an entire group (not just a family). So, what about gift economies?

Gifting on the Playa. [photo: Bill Dimmick on Flickr CC licensed]

“Gifts in Burning Man culture are offered unconditionally. In the case of individuals who contribute to our community, such gifts are relatively easy to accept, and it is only common courtesy to recognize these givers and their contributions. …This is an application of the Principle of Radical Inclusion” (Harvey; Accessed June 17, 2020).

“These remarks on the scientific community are intended finally to illustrate the general point that a circulation of gifts can produce and maintain a coherent community, or, inversely, that the conversion of gifts to commodities can fragment or destroy such a group. To convert an idea into a commodity means, broadly speaking, to establish a boundary of some sort so that the idea cannot move from person to person without a toll or fee. Its benefit or usefulness must then be reckoned and paid for before it is allowed to cross the boundary” (Hyde, 2009).

Understanding gift economies

Gift economies span from indigenous peoples to science cohorts, with Burning Man in the mix, somewhere. Speaking of indigenous gifting, Kimmerer notes; “The essence of the gift is that it creates a set of relationships. The currency of a gift economy is, at its root, reciprocity. In Western thinking, private land is understood to be a ‘bundle of rights,’ whereas in a gift economy property has a ‘bundle of responsibilities’ attached” (Kimmerer, 2013). A great way to dive into the academy gift economy is to read Lewis Hyde’s (2009) book, The gift: Creativity and the artist in the modern world. In his book, Give and Take, Grant (2013) explores giving as a socially valuable practice for 21st Century commerce. Both Hyde and Grant use gifting to illustrate the value of “openness.” For Hyde, openness produces scholarly objects that grow in value as they are shared without regard to direct compensation. For Grant, openness creates weak ties across vast networks where generosity is also generative for creativity and innovation.

A gift economy uses gifting as its primary, and/or its celebrated form of exchange. There are no purely gift economies; people create exchanges for complex reasons that might not fit in this description, even when they use gifting for most exchanges (Graeber, 2001). At Burning Man, where you can find someone to gift you any recreational drug you might desire, you can always purchase coffee at Center Camp. Gift economies co-exist with other forms, such as market economies. Hyde (2009) calls this a “mixed” economy.

In a non-gift economy, gifts can still be reciprocal, even if the return gift is only an expected “thank you.” Families may send out holiday cards and keep careful track of the cards they receive in return. They trim their card list accordingly. Birthday gifts or dinner invitations to friends open up expectations of similar goods coming back. Edge cases are also available. Oprah Winfrey added to her fame by giving away cars (accessed 06/20/2020) on her television show. Philanthropy channels donations to a range of causes where the return is not a gift, but some resolution of a deficit or a wrong. In what way is gifting essential to the academy?

The idea here is simply to catch the central meaning of what a “gift” is within a scholarly community. Hyde points back to Warren Hagstrom’s work on The Scientific Community (1965): “Hagstrom writes that ‘in science, the acceptance by scientific journals of contributed manuscripts establishes the donor’s status as a scientist — indeed, status as a scientist can be achieved only by such gift-giving — and it assures him of prestige within the scientific community’” (Hyde, 2009). However, this exchange of status for the gift of a research article was, and never is that simple. The bundle of responsibilities in this exchange includes (not exclusively) assurances of research integrity, access to data (optimally), and continuing conversations about the research results. The community gets to demand what it needs to realize the value of this gift for science.

Demand sharing is different

Demand sharing is focused on a relationship between individuals and the group. Whereas a gift economy can be focused on how particular transactions are handled between individuals across their lifetimes, demand sharing is grounded on belonging to a group and knowing when and how to offer and to ask for goods from the group. You could say this is a certain form of gift economy, with added group-sanctioned cultural practices. Social distancing during a pandemic is a type of demand sharing. In this case, the group benefits when each individual participates, and the individual benefits when the whole group acts in concert.

Demand sharing resembles “tolerated scrounging” (Widlok, 2013). There is no score to keep, as in monitored reciprocity, and no specific value attached to the goods, as in a market. In place of these are cultural practices and norms that work to preserve the process of sharing, guarantee sharing to all individual members, and protect the integrity of the shared resource pool through active governance. This is precisely what “commoning” in the academy supports (See: scholarly commons).

On the open science expedition, nobody gets left behind

Demand sharing is the economy for the commons

Demand sharing practices require active cultural intention to remain clear and durable. You cannot put demand sharing on autopilot. Rules are less useful here than strategies (See: Making statements about open science). One non-hunter-gatherer example of demand sharing is what is called “expedition behavior.” “Expedition behavior involves putting the group’s goals and mission first, and showing the same amount of concern for others as you do for yourself. Jeff Ashby, a NASA space shuttle commander who has flown more than four hundred orbits around Earth, says that ‘expedition behavior — being selfless, generous, and putting the team ahead of yourself — is what helps us succeed in space more than anything else.’“ (Grant, 2011). Expedition behavior also demands that the group leave no expedition member behind.

Demand sharing begins with a recognition of the legitimate demands from others. It is other-focused. Instead of serial, disengaged market transactions that have no consequent advantage for the group, demand sharing requires and rewards engagement with others. Consideration of others, and consequent consideration by others, creates social closeness: it is a holding close of others into a sharing society.

Demand sharing has been “operationalized” in smaller societies for millennia. Demand sharing practices are local and as complex as their locale requires. “…sharing is in itself a complex phenomenon, more complex than usually imagined by those who are not participating in the economy of sharing on a daily basis” (Widlok, 2016). Responding to the specific demands of research arenas, science also groups its activities into smaller societies of researchers that share their own province of the infinite game — their own precinct of phenomena, theories, and methods. Within and among these groups, demand sharing practices will become as complex as required to fulfill the needs of the group to discover, access, and mine their shared resources.

“A basic goal of provisioning is to reintegrate economic behaviors with the rest of one’s life, including social well-being, ecological relationships, and ethical concerns” (Helfrich and Bollier, 2019).

Investing in, provisioning from, and sustaining scholarly commons in the infinite game

The main kind of “demands” in a demand-sharing academy are demands that new research be shared with colleagues in a manner that promotes rapid reuse and further knowledge generation. You can consider these as “investment demands.” These demands provide a valuable return for each individual scholar and team, which only need to add their work into a shared repository in order to get culturally-supported access to the entire corpus. You add your “carrot” (or onion, or whatever) to the shared research soup bowl, and you get a whole meal back. Only this bowl is never empty, as its ingredients are digital and non-rivalrous. So, you get a shared abundance of meals. These are “provisioning demands.” You get your fill of the latest data and research findings from across the planet.

A second group of demands center around playing the infinite game of science (See: Open Science and the Infinite Game). Within a culture of demand sharing, scientists and teams can demand that their institutions support science across its horizons, and through time within and beyond the lives of individual scientists. This means reaffirming those freedoms that allow science to advance at its own pace and without external influence, and provisioning science teaching and research as a public good (Newfield, 2016). These new demands might include a durable, guaranteed minimum income for all researchers, say, and more university funds for new projects and science infrastructure. Freed from the enormous friction of self-interested finite games where stealing ideas and the fear of “getting scooped” guide a lack of sharing (Hyde, 2009), the academy can focus on stewarding its resources and mining new knowledge from these.

The third group of demands are governance and stewardship responsibilities and activities that require individuals as commoners to work to maintain pooled resources and effective governance strategies across time. This governance “overhead” is inherently problematic when the pooled resources are open to all to use. One solution to this problem is to localize the resources (Neylon, 2017) and task those who use them a lot to step up and be more active in their stewardship. This is one functional reason why scholarly commons (plural) will need to be localized for governance, and globalized for impact. The immediate issue this solution creates is the need for robust interoperability among the commons, including some sharing of cultural norms for mutual use of combined resources.

The last demands are really the first ones in the careers of scientists: the demands that students make on their teachers and schools to provision their learning path. If “tolerated scrounging” describes how scientists gather their research goods, teaching the next generation of scroungers means more than opening up scientific content access and understanding. Open-science teaching includes inculcating cultural knowhow about the norms and practices of commoning in scholarly commons.

References

Graeber, David. Debt: The First 5,000 Years. Brooklyn, N.Y: Melville House, 2011.

— — — . Toward an Anthropological Theory of Value: The False Coin of Our Own Dreams. New York: Palgrave, 2001.

Grant, Adam M. Give and Take: A Revolutionary Approach to Success. New York, N.Y: Viking, 2013.

Hagstrom, Warren O. The Scientific Community. New York: basic books, 1965.

Helfrich, Silke, and David Bollier. Free, Fair, and Alive: The Insurgent Power of the Commons. New Society Publishers. 2019.

Hyde, Lewis. The Gift: Creativity and the Artist in the Modern World. Vintage, 2009.

Kimmerer, Robin Wall. Braiding Sweetgrass: Indigenous Wisdom, Scientific Knowledge and the Teachings of Plants. Milkweed Editions, 2013.

Newfield, Christopher. The Great Mistake: How We Wrecked Public Universities and How We Can Fix Them. JHU Press, 2016.

Neylon, Cameron. “Sustaining Scholarly Infrastructures through Collective Action: The Lessons That Olson Can Teach Us.” Preprint. Scientific Communication and Education, March 14, 2017. https://doi.org/10.1101/116756.

Peterson, N. “Demand Sharing: Reciprocity and the Pressure for Generosity among Foragers.” American Anthropologist 95, no. 4 (1993): 860–874.

Widlok, T. Anthropology and the Economy of Sharing. Routledge, 2016.

— — — . “Sharing: Allowing Others to Take What Is Valued.” HAU: Journal of Ethnographic Theory 3, no. 2 (2013): 11–31.

Open science builds scholarly commons (plural) across the planet

 

PLEASE NOTE: This is a draft of a bit of the Open Scientist Handbook. There are references/links to other parts of this work-in-progress that do not link here in this blog. Sorry. But you can also see what the Handbook will be offering soon.

“We see a future in which scientific information and scholarly communication more generally become part of a global, universal and explicit network of knowledge; where every claim, hypothesis, argument — every significant element of the discourse — can be explicitly represented, along with supporting data, software, workflows, multimedia, external commentary, and information about provenance. In this world of networked knowledge objects, it would be clear how the entities and discourse components are related to each other, including relationships to previous scholarship; learning about a new topic means absorbing networks of information, not individually reading thousands of documents. Adding new elements of scholarly knowledge is achieved by adding nodes and relationships to this network. People could contribute to the network from a variety of perspectives; each contribution would be immediately accessible globally by others. Reviewing procedures, as well as reputation management mechanisms, would provide ways to evaluate and filter information.”-FORCE11 Manifesto

“For the first time ever, the Internet now offers the chance to constitute a global and interactive representation of human knowledge, including cultural heritage and the guarantee of worldwide access”(Preface to the Berlin Declaration on Open Access to Knowledge in the Sciences and Humanities, 2003; Accessed April 13, 2020).

“Scholarly communication should expand the knowledge commons. Scientific knowledge is critical for the development of society. As scientific knowledge is intangible in nature, its use by one person does not preclude its use by another person. On the contrary, knowledge tends to grow when it is shared. Therefore, no barriers should be established to restrict the use and reuse of research results. Scientific knowledge should be a public good and as such part of the knowledge commons, in order to enable everyone in society to benefit from this knowledge.”-Principle #12, Innovation, Vienna Principles

…About beaches: these photos are of beaches in California, where the entire coastline is a public commons.

Starting points toward commoning in open science

In the following, “commons,” “academy commons,” “scholarly commons,” and “science commons” refer to any commons created to house academic shared-pool resources and governed by a community that uses these for their research.

· Science is intensely personal. Scientists are already engaged in their own struggle with the unknowns of nature in the infinite game. Science — their intellectual disease — is fortunately incurable, and likely pandemic.

· Science is already social. Just in the US, several thousand workshops a year evidence the scientific need/desire to build collective knowledge.

· Science is cultural. Self-governed science communities can use intentional cultural practices to help scientists prepare to work together in virtual organizations with shared norms and resources.

· Commoning communities open up arenas for online collaboration. Online conversation-driven collectives supported by virtual communities on internet platforms can replace expensive in-person workshops and massive annual meetings, and enable scientists to share knowledge and solve problems today across the globe.

· These communities need to consider themselves as commons to replace institutions that have been twisted by the three dimensions of external goods and influence (hierarchy, intellectual property, and neoliberal economics). Commons can address the many intellectual property wrongs that plague the academy today.

· Each commons needs to work locally, attuned to its local situation within science domains and academic institutions.

· The academy needs to harness the internet and technology platforms to knit together localized science/data commons into a global web of open shared resources and collective intelligence.

Scholarly commons are…

Intentional communities (plural) formed around the shared use of open scholarly resources (a type of common-pool resource). Commoners work together as a community to optimize the use of the open resources they share. Scholarly commons are resource-near communities. They have an immediate and professional stake in the open resources they need to use for their research. The whole community assumes a stewardship role toward these resources. These groups are self-defining and self-governing, each with their own emergent rules.

Since scholarly commons are usually built upon open public resources, anybody on the planet can access them. When these are digital resources, they are not diminished by overuse. However, these resources cannot be sustained without the commons, or some other economy. These commons represent the social/cultural destination for any number of open-science efforts.

Scholarly commoners are…

Members of these intentional communities, with the freedoms and responsibilities that their communities provide and demand. Commoners work for the benefit of the whole community and for the sustainability of its open, shared scholarly resources. An individual commoner may belong to several commons. It is the role and the goal of commoners to help these open, shared resources flourish.

Membership is implicit in a commons, and represents an active agreement to respect and celebrate the shared principles of the group. Membership will also require some attention commitment to governance and service.

Scholarly commoning is…

The practice (and an attitude) that commoners bring to the scholarly commons. It begins with a logic of abundance, and depends on an active culture of sharing. Commoning is the activity to build and sustain the commons through shared practice (thanks to Cameron Neylon for this wording). Scholarly commoning is also imbued with an ethos of scholarship/science (however defined). Scholarly commoning informs how science can be accomplished through the use of open, shared resources (open ideas, open data, open software, open workflows, open-access publishing with open review, etc.) inside commons, instead of through other types of economies.

Let’s now explore in some depth what commons look like and how they work toward “science done right.”

Commons start with people: a community of commoners.

To paraphrase Peter Linebaugh (2014): “there is no commons without commoners.”

Commoners contribute to and help govern their commons in many ways. They contribute a wide range of research-related objects and data; they ensure that these are sharable and discoverable through the use of appropriate metadata; they create “cerebration” events (See: Knowing and Conversation) to share ideas and scholarly objects, they collaborate in the development and use of appropriate standards and stewardship efforts; they acknowledge the efforts of others in their work; they promote the commons and commoning as a mode of scholarly effort.

Because commons are owned and led by their communities, volunteers are given the responsibility to envision, build, and govern these as destinations for the future of open science and scholarship. All commoners will benefit from the impacts that their commons will make on the academy’s research and communication capabilities. Volunteer leaders will also gain satisfaction that their time and efforts will grow these resources for the benefit of all and the advancement of knowledge.

A text with some history

The text below originated from an early-draft document entitled Principles of the Commons, put together by various contributions to Force 11 working groups over the past six years. That draft version of the Principles of the Scholarly Commons was based on the workshop Re-imagining Scholarship held by FORCE11 in Madrid, Feb 2016 and further refinement by the Scholarly Commons Working Group. The original Google Document for this was the product of unattributed contributions by several people, it is borrowed for the Handbook. You can check in on the current work of this endeavor here. Hop on and add your ideas.

The text has been highly revised and edited to introduce the central tenets of academy commons and commoning for this Handbook. PLEASE NOTE: The text no longer expresses the recommendations and wording of the Force 11 document.

“Before every great idea is a crazy idea.”
Jono Bacon (2009)
“The world’s cognitive surplus is so large that small changes can have huge ramifications in aggregate.”
Clay Shirky (2010)

These commons are open to all participants who accept their principles

Commons can support a diversity of skills and knowledge without privileging any. All commoners will find a home for their knowledge and their interests. As a norm, participation in any scholarly commons is not restricted on the basis of accreditation, professional standing or reputation, or any other criteria except willingness to contribute and uphold the principles of the commons. Content and behavior are the only criteria for moderation within a commons.

Commons are intellectual “rooms” (See: Science happens elsewhere) that value active sharing and collaboration. Commoners serve these requirements in different ways across the spectrum of occupations and career paths. A commons does not require a specific volume or genre of contribution, a particular professional, educational, or social background, affiliation, certification, or status.

The reach of the global commons network is not restricted to participants from any single sector or region. This network provides a home for the work of full professors, citizen-scientists, entrepreneurs, and bloggers. It recognizes the comment, the scholarly monograph, the dataset, the discussion, and the commercial product or service. It provides a home and recognition for programmers, statisticians, bench scientists, and literary critics. It welcomes the most narrowly focused specialist work and the broadest popularization. Above all, it encourages commoners to collaborate and share their specializations and interests.

Each commoner gets more value than they give as they grow their scholarly commons (note: any scholar may belong to more than one of these). The return on investment (ROI) for the commoner demonstrates how a commons as a whole is more valuable than any of its pieces. One part of this equation is due to the power of pull (See: Demand sharing and the power of pull), which amplifies the value of participation, and also the utility of each object being shared in the network.

Commons are self-identified by interests, disciplines, experiences, data sources and uses, and research goals. Commoners across the planet will be linked as their local commons builds networks with other commons to expand the “room” they share to animate their conversations and creativity.

“Definitions belong to the definers, not the defined” Toni Morrison.

Science commons welcome and encourage participants of all backgrounds

Fierce equality (See: Fierce Equality) means that every commons welcomes and encourages participants of all genders, social, regional, ethnic, linguistic, and disciplinary backgrounds. It also recognizes that disagreement is an inherent part of research communication, including disagreement as to fundamental principles and theories.

A commons is an ecosystem that is defined by the interactions of each and every commoner who participates in jointly building and governing it. Just like every other ecosystem, a commons cannot be a monoculture; instead, it needs diversity in order to survive and thrive. While many scholarly disciplines differ in their culture of how to generate, treat and store their scholarly objects, their commons must be open to all of them.

In a similar way, scholarly commons can not only rely on the expertise of traditional scholars. Instead, they need to be open and accessible to commoners that don’t fit the academic stereotypes, or indeed never were in academia. Creating scholarly objects and performing scholarly activities is not limited to the traditional academic scholarly community. This means that commons must be open to non-traditional research questions and answers, including those proposed by non-professionals.

Through its self-governance, a commons uses vigilance with regard to hidden and structural biases and impediments and humility and open-mindedness with regard to the life-experiences of others. Because a commons is a shared agreement, the onus for ensuring equality and diversity of access is on the commoners themselves.

As commoners build self-governance, they should consider statements on inclusivity and language policy, because these encourage critical reflection on structural impediments. Exclusion of participation based primarily on formal degrees and academic rank is discouraged. When such criteria are used, alternative routes to participation should be provided.

Equality also for objects in the pooled resource collection

Commons accept all contributed objects that adhere to their guidelines on an equal basis regardless of form

In order to improve the breadth and pace of knowledge generation, a commons will accept any contributed object that adheres to its guidelines. Because commons are grounded by a logic of abundance and a goal of reuse, they do not serve as gatekeepers or pretend to know the ultimate knowledge-value of any of their shared objects.

This means that there is no test of value, impact, significance, relevance, or endorsement that can be used to determine what belongs within a commons. Blog postings are as eligible as scholarly monographs. Highly cited papers are as welcome as preprints. Ground-breaking studies are as welcome as replication studies.

Once an object is in a commons, it is available for additional services. For example, commons services could be implemented to help commoners search for objects. Early versions of objects can be peer-reviewed. Objects can earn citations. Objects may be further curated or aggregated into collections by other commoners based on their expertise. Data objects can be evaluated for provenance and various qualities that improve their use and reuse.

Some services will not be provided inside a commons. For example, others in the academy may want to add metrics or rankings to objects in a commons. Commons have no objection to these services, however all forms of metrics should be built on transparent and open standards so that they may be reproduced and understood. Rankings will be made external to a commons and will not be housed inside the commons.

John Wilbanks: “Going back to the beginning of science: it used to belong to all of us.”

Smaldino and McElreath (2016): “when a measure becomes a target, it ceases to be a good measure.

“We reaffirm the principle that only the intrinsic merit of the work, and not the title of the journal in which a candidate’s work is published, will be considered in appointments, promotions, merit awards or grants.”-Bethesda Statement on Open Access Publishing, 2003; Accessed April 9, 2020.

“Do not use journal-based metrics, such as Journal Impact Factors, as a surrogate measure of the quality of individual research articles, to assess an individual scientist’s contributions, or in hiring, promotion, or funding decisions.”-DORA; Accessed April 9, 2020.

Science commons have no intrinsic hierarchies, rankings, or reward systems

All participants and all research objects that conform to the principles of the commons are equally appropriate and available for dissemination and reuse. Attribution systems and formats are driven by the demands of transparency and the intrinsic nature of research, rather than the requirements of any reward system. Intellectual humility (See: Kindness, Culture, and Care) is expected in these commons as internal good and a norm for science, crowding out bullshit prestige.

All contributors are acknowledged on an equal basis (meaning there is no intrinsic difference between authorial and other acknowledgements); all forms of dissemination are accepted on an equal basis (meaning there is no hierarchy among genres or formats). Commoners are expected to match the form of dissemination to the needs of the research output rather than the demands of a reward system. None of this is compatible with systems that create hierarchies among types or forms of contribution or encourage dissemination in one format over another.

The fundamental premises of a science commons are incompatible with “scooping”, because the commons does not require these ideas to be new or unique as a condition of entry, even though the commons tracks when and where ideas and objects enter the commons.

“…[I]f we could solve the problem of open access within the university — that is to say, prove that the economic equation of doing research, reviewing it, and making it freely available for everyone works, then we could prove that the tyranny of the margin need not operate everywhere.” (Kelty, 2014)

“Our mission of disseminating knowledge is only half complete if the information is not made widely and readily available to society.”-Berlin Declaration on Open Access to Knowledge in the Sciences and Humanities; Accessed April 9, 2020.

“Computer analysis of content in all formats, that is content mining, enables access to undiscovered public knowledge and provides important insights across every aspect of our economic, social and cultural life.”-Hague Declaration on Knowledge Discovery in the Digital Age; Accessed April 9, 2020.

“When intellectual property law allows content to be read and analysed manually by humans but not by their machines, it has failed its original purposes.Hague Declaration on Knowledge Discovery in the Digital Age; Accessed April 9, 2020.

A commons is open by default, with a culture of demand sharing

Openness for demand sharing (Demand Sharing) is the core norm for a commons. Its resources are intentionally and reflexively open and entirely free to use, read, reuse, and remix by humans and machines, unless there is a compelling reason to restrict access, e.g., personal health information. Scholarly commoning starts with openness as a norm, and supports activities that explore open scholarship fully. Demand sharing is the main activity in a commons.

Commons can use standards and guidelines developed by other organizations (e.g., OKFN Open Definition, Budapest Open Access Initiative guidelines, and the Open Source Initiative definition) to inform their core definition of open content and access. Openness will be reinforced through the use of licenses that support the sharing of outcomes, such as knowledge gained by mining commons resources, research undertaken using commons resources, and software derived from commons code.

Commons will support a variety of open licenses. In their daily practice, commoners heed the requirements of these licenses and add their own content through them. Open includes promoting machine access to resources and metadata. Openness includes the right to deposit as well as to access, read, analyze, cite, quote, and mine. Where privacy is important to protect the rights of data providers or subjects, commons will make best-practice efforts to secure these data.

Demand sharing necessitates a radical rethink by stakeholders in their relationship with research assets produced by ‘their’ researchers, using ‘their’ funding, published within ‘their’ publications. The openness of commons allows the development of external services that can be more closed, proprietary, or involve ranking and selection: e.g. aggregation and indexing services, as long as they do not devalue the commons.

“In many instances IPRs [intellectual property rights] appear to be privatizing and commoditizing — “enclosing’’ — socially useful knowledge that, if widely shared, could result in more affordable and accessible medicines, scientific research, educational resources and climate technologies. In recognition of this reality, EU policy ought to empirically examine whether existing policies are sanctioning severe opportunity costs. By recognizing contemporary technological and economic realities, EU policies could unleash moves towards more affordable health systems, wider uptake of green technologies, a more open, participatory creative culture, and more responsive democratic governance” (The EU and the Commons, 2015; Accessed April 12, 2020).

Any person, organization or other entity can make scholarly work public.

As long as the criteria for open sharing are met — as determined by each commons through their governance — making a work publicly available is considered publishing a work. Additional requirements to add value for reuse (metadata, provenance, reproducibility, etc.) increase in value in a demand-sharing science culture, where outputs can be mined, mixed, and repurposed. Any person, organization or other entity (including publishing companies or entities that currently act as such, e.g. scholarly societies) will be welcomed by commons for providing services that help the publication, preservation, dissemination and assessment of scholarly work, as long as these services and the outputs they produce comply with the demand-sharing principles of the commons.

As commons content is stewarded by commoners within the commons, exclusive rights to this cannot be sold within or without the commons. Fees for additional services designed to maintain shared resource availability can be managed within the commons. Fees for access outside of the commons, and outside of the larger networked commons endeavor can be used to fund commons expenses, but cannot restrict access to content inside the commons. Operational principles for those who provide infrastructure for a global scholarly commons network are laid out in Bilder, et al, (2015).

Science commons explicitly reject the current model of publishing scholarly works which emphasizes the release of works only when they have undergone the peer review process. In a commons, a published work may be a version of a work that gets subsequently refined, similar to the way that open source software is released and then refined. Additional layers of curation, peer review and editing will be performed on works as needed for purpose. Note that these comments, discussions, annotations are themselves scholarly objects.

“Building a small ecosystem of capped returns is all well and good, but it won’t make much of a difference in the grand scheme of things. This idea has the most potential for impact if it becomes the new norm and displaces indefinite returns significantly — maybe entirely.” P2P Wiki

Effective institutions at all levels require continuous engagement, because they all unravel over time.” (Benkler, 2015)

A country, after all, is not something you build as the pharaohs built the pyramids, and then leave standing there to defy eternity. A country is something that is built every day out of certain basic shared values.” Pierre Trudeau.

“Communal values must be taught, and renewed, continuously.” (Peter Linebaugh, 2014)

Sustaining scholarly commons: There is global commitment and participation in long-term viability and preservation.

A global community is needed to actively grow and sustain science commons in the long-term. The shared-pool resources of hundreds of commons across the planet will need, and should command public funding for maintenance and growth. Each state has a stake and role in preserving and promoting the active knowledge available through commons repositories hosted in their territories, for the benefit of all science.

Commons will not flourish without the participation of commoners within the commons and also as citizens of their polities, promoting commons norms and values across societies. Commoning as a feature of scholarly work needs to be taught at all levels, practiced in everyday work, discussed and improved through reflexive innovations, and celebrated across the globe.

“An economics of abundance seek out these kinds of strategies of providing for our needs; it is not an economics that assumes that abundance exists, but one that analyzes modes of scarcity generation…, and that points out ways to counteract them” (Hoeschele, 2016).

“It seems like if we could re-frame the way we think about these problems, and find new abstractions, new places to stand and see the issues we might be able to break through at least some of those that seem intractable today. How might we recognise the unexpected places where it is possible to create abundance?” (Neylon, 2015); Accessed April 9, 2020.

All activities and outputs that take place within commons have a permanent home in these commons and are available to the public

All content and services in scholarly commons will be publicly shared. All resources are openly available and may not be removed. There is, of course, a differential built into the amount of prior learning that enables various uses for commons resources. Mostly this is a built-in feature of the complexity of the research endeavor, and the extreme complexity and emergent qualities of the current state of research in any field. A chess club may be open to all, however, the skills needed to play well with the most advanced members become available mainly through long-time learning and practice. Similarly, optimal use of scholarly commons resources very often requires years of training/learning. See also: Against Exclusion: open is open to all.

Currently, academic research is surrounded and interpenetrated by an economic logic that manufactures scarcity as a means to grow arbitrary value and improve profit margins. The academy needs to grow its own digital economy. And for this, it needs to capture the value that researchers invest into it. One part of this exchange value will come from the expansion of internet-enabled services, another from the increase of its digital resources, and a third from the contributions of scholarly talent and funding sources.

While it is tempting to try and capture more value for pooled resources inside a commons by creating a differential use license that restricts use outside of the commons, there are more effective means available for this purpose. Commons can create or participate in civic trusts, set up like land trusts are today, which hold key aspects of the property rights for commons resources, and can negotiate with other commons and with external interests for the use of these resources (See: McDonald, 2015; Accessed April 10, 2020). Cultural practices that support demand sharing within commons can also be effective in reducing behaviors such as extracting resources from the commons or seeking advantages by working with external interests.

With ‘subtractive’ resources such as fisheries, for instance, one person’s use reduces the benefits available to another. High subtractability is usually a key characteristic of common-pool resources. Most types of knowledge have, on the other hand, traditionally been relatively nonsubtractive. In fact, the more people who share useful knowledge, the greater the common good” (Hess and Ostrom, 2009).

Demand sharing means that the use of commons resources cannot devalue these

The logic of scholarly commons starts with the notion of abundance. One mission of scientific commons is to manage a full range of science objects, without needing to reject some because of an arbitrary constraint on capacity or a responsibility to judge their value. The aim then is to maximize the usefulness and usage of these objects by supporting discoverability, mining, sharing, and reuse. Unlike natural resources (a fishery, a forest, etc.) the digital objects in scholarly communication are non-rivalrous. Their use by one member does not devalue their use by another. Overconsumption is not a concern. The optimal state for the global network of scientific commons is one that supports as much consumption of their resources as is technically possible (See: Abundance).

In any one commons, the active sharing of resources, and the added opportunities for creative conversations and “cerebrations,” produces a great variety of outcomes and records, and new generations of results that had been enabled by the commons, and that get returned to start new cycles of knowledge building and knowing. Every commons anchors deeply into the infinite game being played by its members. Each commons reaches out to other commons to expand the horizon of the infinite game of science (See: Open Science and the Infinite Game). In some ways, each commons is self-sustaining: a crucible of activity and joy that fuels itself.

Do-ocracy: “Responsibilities attach to people who do the work, rather than elected or selected officials.” P2P wiki.

There is an expectation of service by commoners to support research and scholarship in their commons

Commons will establish their own forms of do-ocracy. This is a generalizable feature of self governance for any scholarly commons. Leadership will be gathered from the edges, where new working groups will be building and expanding the collection and its services. Effective group leaders will find that their service opens up new doors for greater service (no good deed goes unpunished). A reputation for accomplishing significant work will form the basis for participation in leadership roles.

Scholarly commons build on a tradition of service; scientists have been gifting their research results to the republic of science for centuries now. The types of activities that constitute service are expected to be enlarged and their capacity for documentation enriched, e.g., participation in online conversation forums. As a general rule, individual scholars and teams will always receive more value from their commons than they contribute. This primary surplus of value is not just due to the network effects of commons (network effects), but also from the added opportunities for serendipitous interactions (Serendipity). The value proposition that each vibrant commons represents can be expressed explicitly on an individual, institutional, functional, disciplinary, national and global basis.

Single loop organizations fix problems… Double loop organizations fix problems and fix the situations that caused the problems” (Shirky, 2011; Accessed April 12, 2020).

“[P]rofessions have specific ‘internal goods’. They include truthfulness, analytical skill, and buying into the professional’s fiduciary duty to their client in the wider context of behaving with integrity to all. To acquire such internal goods of practice — or ‘goods of excellence’, as he subsequently termed them — MacIntyre [1984] argues that one must practice at least three virtues: justice, courage and honesty.
When practising one’s profession, one can’t make up one’s own facts. And a good argument is one that would persuade the best of one’s colleagues, not just one’s own side. Thus, just as Francis Bacon proposed — sublimely — regarding the growth of science, that we cannot command nature except by obeying it, so the professional must master and obey the imperatives of their discipline to gain access to the agency it offers. This idea of engaging with an external or objective order implies justice, which is secured only by allowing correctness within the practice to trump ego or power. This, in turn, implies equal treatment for equal merit within the terms of the practice” (
Gruen; Accessed April 14, 2020).

Commons become community-based value-generators for the work of their members

The way forward requires an effort that spans the entire practice of scholarship, from intellection to publication. Researchers face the task of redesigning the scholarly workflow, while they inject these new modes of doing research and publication into the broader academy. The life of a scholar is rigorous and difficult, but also includes opportunities for personal and collective fulfillment. As commons spread across the academy, these will generate local communities that do two important tasks for each member: the communities cascade collective meaning into scholarly practice at the team, and they support cultures of caring and kindness, and trustful events and friendships. They hold shared, internal virtues (goods) as binding on their members. As MacIntyre (1984) reminds us: “[T]he essential function of the virtues is clear. Without them, without justice, courage and truthfulness, practices could not resist the corrupting power of institutions.”

Virtues and normative practices in a commons are promoted to stimulate behaviors that support the production and dissemination of the best scholarship and science. They encourage respect for the principles of these commons, and they discourage behaviors and practices that inhibit participation. They apply to all stages of and participants in the research cycle. They respect and support non-standard research outputs (such as datasets, software, methods, null-results, ideas) and para-scholarly activity (e.g. leadership, community service, peer review, and adjudication).

Researchers across the globe will have wide variety of local issues to bring to their commons. The academy today is broken in various ways that reflect cultural issues locally. Each organization and discipline faces their own version of these disfunctions. While all solutions are ultimately local, every commons creates helping practices that can be shared laterally across the planet.

“What I call software collapse is what is more commonly referred to as software rot: the fact that software stops working eventually if is not actively maintained. The rot/maintenance metaphor is not appropriate in my opinion because it blames the phenomenon on the wrong part. Software does not disintegrate with time. It stops working because the foundations on which it was built start to move. This is more like an earthquake destroying a house than like fungi or bacteria transforming food, which is why I am trying out the term collapse” (Hinsen, 2017: Accessed April 13, 2020).

“How do we ensure that the system is run “humbly”, that it recognises it doesn’t have a right to exist beyond the support it provides for the community and that it plans accordingly?” (Bilder et al, 2015).

Scholarly commons exist outside of specific technologies, funding sources, and business models

Scholarly commons accommodate, facilitate, stimulate and adapt to any developments and technologies that promote their goals, and enable their practices. Because the needs of commoners and the means to meet these will be emergent, commons must remain nimble and able to pivot. Commoners are stewards over their shared-pool resources. They treat these with the same quotient of caring that they bring to one another. Commoners are maintainers as well as innovators.

Commons can also fail. They can lose the capacity to own and steward the shared pooled resources they need; this will happen should their resources become “enclosed” by another organization (e.g., when these are sold to a for-profit concern). Or, a commons can fail to sustain their governance model and lose the necessary volunteer support and membership. When a commons fails, it is important that pooled resources remain in the civic trust, so that a new commons can be generated as needed to manage these. A single civic trust (Accessed June 12, 2020) can hold the property rights for one or many commons, each of which has access to the shared resource. This also reduces the transactional value of the commons, since the commons owns mainly the right of access (including mixing and mining, etc.), and the trust owns a portfolio of other rights. The trust guards against enclosure of the commons’ resources, a major cause of failure.

Other ideas/questions about commoning in the academy:

· A single object — say a dataset — in one open repository can be claimed as a resource by more than one commons, as long as each commons supports their own dark archive, or points to a collective dark archive, in case of data loss.

· Scholarship needs to be fearless in its infinite game play. One role of academic tenure was to protect this condition. In the face of the neoliberal market, tenure has failed in this role. Hundreds of thousands of scholars will never achieve tenure. Can the commons provide this protection?

· Someone noted that many science data objects are “uncommon” objects that require knowledge and knowhow to use and share. Scholarly commons also maintain knowledge and knowhow along with its shared resources. Commoners are maintainers too.

Moving ahead

The real question is how to rescue (or re-place) current academic institutions using commons-based societies and economics. The commons is not an alt-academy, it needs to refactor existing organizations, where possible, and spin up new ones as required. How can we help move this process forward? If commoning is the “WD40” to release science for the sclerotic hold of its 19th Century institutions (See: Is my learned society obsolete?), internet-based technology is the duct tape needed to help these hundreds and thousands of commons communities work in concert across the globe. The internet holds the future of science. Shared resource platforms, such as Zenodo <https://zenodo.org/> can operate at a global scale when needed, and support thousands of small teams as required. For commoning to gain traction in the academy, we must explore commoner-owned online platform cooperatives (Smichowski, 2016) as a generative practice for open science.

The first step is culture change: we need to unleash a more profound understanding of the circumstances of scholarly commoning by building up new open practices, informed by fierce equality (Fierce Equality) and demand sharing (Demand Sharing). These efforts will be localized and applied as needed to yank local institutions away from hierarchy, intellectual property wrongs, and the pull of the margin that preempts ethical decisions and norms.

References

Bacon, Jono. The Art of Community: Building the New Age of Participation. Sebastapol:OʼReilly. Available At, 2009. http://www.artofcommunityonline.org/downloads/jonobacon-theartofcommunity-1ed.pdf.

Benkler, Yochai. “The Idea of the Commons & Future of Capitalism.” Presented at the Creative Commons Global Summit Seoul, Korea, October 15, 2015, 2015. https://www.slideshare.net/cckslide/the-idea-of-the-commons-future-of-capitalism-yochai-benkler.

Bilder, Geoffrey, Jennifer Lin, and Cameron Neylon. “Principles for Open Scholarly Infrastructures.” Science in the Open, 2015.

Hess, Charlotte, and Elinor Ostrom, eds. Understanding Knowledge as a Commons. From Theory to Practice. Cambridge MA: The MIT Press, 2009.

Hoeschele, Wolfgang. The Economics of Abundance: A Political Economy of Freedom, Equity, and Sustainability. CRC Press, 2016.

Kelty, Christopher. “Beyond Copyright and Technology: What Open Access Can Tell Us about Precarity, Authority, Innovation, and Automation in the University Today.” Cultural Anthropology 29, no. 2 (2014): 203–215.

Linebaugh, Peter. Stop, Thief! The Commons, Enclosures and Resistance. Oakland: PM Press, 2014.

MacIntyre, Alasdair C. After Virtue: A Study in Moral Theory. 2nd ed. Notre Dame, Ind: University of Notre Dame Press, 1984.

Shirky, C. Cognitive Surplus: Creativity and Generosity in a Connected Age. Penguin UK, 2010.

Smaldino, Paul E, and Richard McElreath. “The Natural Selection of Bad Science.” Royal Society Open Science 3, no. 9 (2016): 160384.

Smichowski, Bruno Carballa. “Data as a Common in the Sharing Economy: A General Policy Proposal,” October 2016. https://hal.archives-ouvertes.fr/hal-01386644.

Joy, fun, and love in open science

How much joy do you get from your research?

“Science functions best when scientists are motivated by the joy of discovery and a desire to improve society rather than by wealth, recognition, and professional standing. In spite of current pressures, it is perhaps remarkable that many scientists continue to engage in selfless activities such as teaching and reviewing, decline to publish work that doesn’t meet stringent standards for quality and importance, freely share reagents and knowledge without worrying about who gets the credit, and take genuine pleasure in supporting the efforts of other investigators. Such individuals should be recognized and emulated” (Casadevall and Fang, 2012).

“Numbers have many charms, unseen by vulgar eyes, and only discovered to the unwearied and respectful sons of Art. Sweet joy may arise from such contemplations.” Charles Babbage circa 1825, quoting French Mathematician Élie de Joncourt, circa 1735 (Gleick, 2011).

PLEASE NOTE: This is a draft of a bit of the Open Scientist Handbook. There are references/links to other parts of this work-in-progress that do not link here in this blog. Sorry. But you can also see what the Handbook will be offering soon.

Start here with joy

While writing this handbook, it became clear that, as a life-way — as a career that is also an avocation — science today needs to rekindle the internal emotional goods that have long been wellsprings for creativity and innovation across the lifetime of the scientist. Science is the hardest thing humans can do, in terms of the challenges it faces, and the obstacles to resolve these. There is no shortage of hard work, long hours, and disappointments available to the scientist. These have been with science since the time of Francis Bacon.

Science is serious. We can take that as given. Science faces many of the hardest and most meaningful questions humans have managed to ask themselves and the universe. What is the origin of life? What is matter made from? Why must we die as we do? But science was never only “serious” in its practice. Scientists get to play the infinite game (See: Learning to play the infinite game), a pursuit that opens up to awe and wonder — and joy — at any time. “Joy has a component, if not of morality, then at least of seriousness. It signifies a happiness which is a serious business. And it seems to me the wholly appropriate name for the sudden passionate happiness which the natural world can occasionally trigger in us, which may well be the most serious business of all” (McCarthy, 2015). Yes, science is serious, but so too is joy.

“Too much of the OA [open access] discussion is grim, utilitarian, and problem-oriented. We should complement it with discussion that is joyful, curious, and opportunity-oriented. Serious problems don’t rule out beautiful opportunities, and one of the most beautiful opportunities facing OA is that certain strategic actions will solve serious problems and seize beautiful opportunities at the same time.” Peter Suber (2012)

Open science will almost necessarily be more joy-full than the science you’ve been doing. Some of this comes from its inherent generosity, and the gratitude you feel at the generosity of others when they share openly the science findings that help your research. “Gratitude is a powerful emotion. We declare that we are satisfied. We can drop our search for more; in this moment, we have everything we need. Out of that fullness, other emotions naturally bubble up. We tend to get in touch with joy and generosity, and we treat others with love and care” (Laloux, 2014).

Open science enables infinite game play. You will be challenged there when nature stays silent to your questions, but you will also find joy. “There can be occasions when we suddenly and involuntarily find ourselves loving the natural world with a startling intensity, in a burst of emotion which we may not fully understand, and the only word that seems to me to be appropriate for this feeling is joy” (McCarthy, 2015) (See also: Popova; Accessed May 31, 2020).

Certainly, there is some little joy in those finite games that scientists play today. However, this type of joy is kept scarce through the logic of “science as a race.” This logic informs scientific research as a series of races, each one ending in the form of some achievement that can be owned by the scientist, and in extension by their home organization. “The contradiction of finite play is that the players desire to bring play to an end for themselves” (Carse, 1987). In order to win, and to feel this variety of joy, they need to hold up their discovery — as a distinct, independent object — for public notice. They seek an audience, and arenas — certain journals, learned society prizes, funding agencies, campus administrators — where their personal winning can be acknowledged with some special notice or title. “If finite players acquire titles from winning their games, we must say of infinite players that they have nothing but their names” (ibid). The winner’s joy is amplified by the number of losers around them. They have succeeded where so many others failed. But the joy of these distinctions is momentary. The next race has already begun.

Joy in abundance

The joy of open science is like the joy of a choir while creating the music they sing together. This joy is fully shared, as a form of collective virtuosity (Accessed June 9, 2020). The better the singers’ voices blend into a single chorus, the finer their song sounds. Should the choir grow larger, the joy only multiplies. Should the song grow longer, the joy only expands. “The paradox of infinite play is that the players desire to continue the play in others. The paradox is precisely that they play only when others go on with the game. Infinite players play best when they become least necessary to the continuation of play. It is for this reason they play as mortals. The joyfulness of infinite play, its laughter, lies in learning to start something we cannot finish” (ibid). Open science is a song with a choir anyone is welcome to join (with some real training behind them), a song that doesn’t end when any one voice becomes silent.

“Specifically, joy may be thought of as delight that arises in response to a source of meaning or value in life. Delight describes a pleasant emotion, conveying the positive valence of joy. Connecting this to a matter of meaning or value differentiates joy from other positive emotions, such as happiness, a more general case in response to anything pleasant; amusement, in response to something entertaining; gratitude, in response to receiving something; pride, in response to accomplishing something; interest, in response to engaging in something, etc.” (Krumrei-Mancuso, 2019).

Under certain circumstances, doing science opens up opportunities — events — for a delight that comes from connecting to nature. “A lot of the time, when you do Math, you’re stuck. But you feel privileged to work with it. You have a feeling of transcendence and feel like you’ve been part of something really meaningful.” Akshay Venkatesh (ICM 2018; Accessed June 1, 2020). Science organizations can be governed to encourage, enable, and celebrate these events.

More importantly, individual scientists need to develop their capacity for joy, a capacity they might have had as a child only to lose during their schooling. Like practical wisdom (The practical wisdom of doing science), you can get better at finding moments of joy in your research and teaching. Of course, going to work in an open-science culture organization does not mean you simply step up to a day of joy. The labors of science are infinite. The disappointments and the setbacks are legendary. All the joys offered in science are earned. “The joy of science lies in pondering the magnificent and seeking answers to the unknown. Indeed, Stephen Hawking’s advice to ‘Look up at the stars and not down at your feet … Be curious’… is not far from what other scientists have noticed drives many scientific discoveries: the experience of awe”(McPhetres, 2019).

One of the goals for culture change in open science needs to be an acknowledgement of the role of intrinsic motivations, and a cultural devaluing of the external, often perverse (Binswanger, 2015), incentives that create so many conflicts of interest today in science. “We call for a cultural change in which scientists rediscover what drew them to science in the first place. In the end, it is not the number of high-impact-factor papers, prizes, or grant dollars that matters most, but the joys of discovery and the innumerable contributions both large and small that one makes through contact with other scientists”(Casadevall and Fang, 2012). Like other psychosocial skills, joy increases across time when you work at it. Fun, however, can erupt at any moment when two or more scientists get into a conversation (or a “cerebration”(Asimov; Accessed May 1, 2020)) about their research.

Are you having fun yet?

“For best purposes [for creativity in a group], there should be a feeling of informality. Joviality, the use of first names, joking, relaxed kidding are, I think, of the essence — not in themselves, but because they encourage a willingness to be involved in the folly of creativeness. For this purpose I think a meeting in someone’s home or over a dinner table at some restaurant is perhaps more useful than one in a conference room” (Asimov; Accessed June 8, 2020).

Science play is serious play

There is a whole literature on “play” and and its valuable role in creativity and imagination from childhood to the board room. Linder, Roos, and Victor (Working Paper, 2001; Accessed June 4, 2020) do a good job of surveying this literature. Their Institute proposed “serious play” as the foundation for strategic thinking. Thomas and Brown (2007) look more specifically at the collective knowing that multiplayer games produce, and how this might inform new theories of learning. Csikszentmihalyi’s work on autotelic, optimal experiences (what he calls “flow”) describes how play — in a wide range of environments, including the workplace — offers its own very important incentives and rewards. His 2004 TED talk is a good starting place. Caron (2017) looks at how the study of society can be based on the cultures of games, as emergent, open-ended, strategic play. Here is it helpful to not contrast “play” with “serious”. Play can be terminally serious; look at sword-play. Play can be artistically virtuosic: as in word-play. Consider open science as full of play: data-play, theory-play, methods-play. Remember too, play is fun. That is a bonus.

Your love of science might have started early

Open-science-culture governed organizations can intentionally, and reflexively promote events where creative folly — the play of intellection — is more likely to occur on a more regular basis. When they abandon the finite games of metrics-turned-into-goals, these organizations will find new spaces and time for serious play. Fun is guaranteed as a first-order outcome, together with more creative imagination, an increase of shared knowing, and the likelihood of better problem solving. Asimov (above) noted that bosses and funders might not fully appreciate the level of fun involved in events of group creativity. He suggested that participants be given “sinecure” tasks — to write a white paper, say, or a final report — something perfunctory to keep the funders happy and the bosses complacent. Never confuse these tasks with the real work, and the serious play of scientific conversations.

It’s clear from the literature that talking about play and fun in the workplace surfaces a tension between two models of academic work. The first model tells us (and our funders) that work needs to be endured. And for it to be endurable in a meaningful fashion, it must be difficult and arduous. No fun allowed. Neoliberal managerial practices serve here to ratchet up demands and metrics to be sure that next year, or next week, you will need to work harder than today. So, buckle up and buckle down, because somewhere else, others are working harder than you are, and you will be left behind, unfunded and tenure-less.

The second model tells us that each scientist has — through many years of learning and striving — earned the right to play the infinite game of science, which has no clock, and runs on shared knowing and ubiquitous doubt. This work is no less arduous. However, there is also laughter and joy, and a love for the process of doing science and for the object of study. “A love of knowledge, the most valuable resource in Universities, is being squandered by policies designed for the market place” (Rowland, 2008). Open science culture change can move your team and your organization from the first model to the second one. This Handbook will help.

Cerebrations are always fun

You don’t love science because it’s fun. You have fun doing what you love. It’s called science.

“The lesson here for Open Scholarship may be that an inherent personal love of science and discovery must be nourished…, and communities that can affect the principles of Open Scholarship must also be cultivated around this” (Tennant, et al, 2019 A tale of two ‘opens; Retrieved September 8, 2019).

In the end, you cannot talk about open science without adding how this enables new/old practices that show the love of science and the love of nature through science. And you can’t really talk about changing cultures in your workplace without asking the question: does this workplace nurture the love that its workers might find, the joy they can feel and share, and the fun they can generate through their work and with their time here? As Roland (2008) notes: “[I]t is somewhat ironic if academics consider a term such as a love of knowledge — or ‘intellectual love’ — should not be taken seriously. It is strange that a phrase such as ‘the delivery of learning outcomes’ is taken to be serious and meaningful, but not ‘inspiring a love of learning’. Has talk of such love no place in the language in which academics write about their work?”

One of the cultural aspects of open science that deserves more conversation is the replacement of external incentives with those internal incentives that have long been a part of science, but which have been demoted and shunted in the pursuit of finite games and the logic of competition. The love of science is a lifetime affair. It probably started for you in childhood. “As researchers we sometimes need to be reminded that we are contributing to an astonishing human effort, which transcends an individual’s lifetime (Frith, 2019). It is a big “why” for those career choices you’ve made. It also promotes trustful, caring relationships with other scientists. There is no room for: “I love science, it’s scientists I can’t stand” (See: Kindness, Culture, and Care). A love of science also opens up an avenue for “slow science.”

It is time to slow down and smell the science

“Science needs time to think. Science needs time to read, and time to fail. Science does not always know what it might be at right now. Science develops unsteadi­ly, with jerky moves and un­predict­able leaps forward — at the same time, however, it creeps about on a very slow time scale, for which there must be room and to which justice must be done.”
From The Slow Science Manifesto (2010).

Sometimes slow is just about right

Open science is not only slow science, indeed, open science looks to accelerate knowledge sharing, but it does foster slow science as a part of the future of how science is done. “This slowing down represents both a commitment to good scholarship, teaching, and service and a collective feminist ethics of care that challenges the accelerated time and elitism of the neoliberal university” (Mountz, et al, 2015). What if each scientist is limited to one published paper a year (with unlimited preprints, blogs, etc.)? What if each scientist can only receive three external grants in their career — and their home organization was responsible to work with funders and the public to increase the general, in-house support for science research? What if teaching the love of science were a large part of career advancement? The cultures of open science will foster emergent practices that can move the academy away from the current the neo-liberal university model.

Coda: I thought science was all about rationality

You could argue that “rationality” is central to instrumentalist practices in science and dominates the explanatory prose of science reports. Useful it is, we will all admit, within its domain. No disagreement here. All of the arguments for precision and intellectual rigor, for “doing the math,” and being grounded in the methods: these are a given. There is not anti-rational basis for open science. The real issue is where rationality fits into the larger practice of science. What are the limits of instrumentalism? Where does imagination and serendipity show up? When do explanations fail? “Indeed the exclusive attachment to purpose, consistency and rationality may be inappropriate in organizational situations that actually require reason’s ‘non-rational’ cousins, including impulse, intuition and lived bodily experience” (Jacobs and Statler, 2004. Working Paper; Accessed June 8, 2020). You can be coldly rational with your research strategies, logical with your data, rigorous with your methods and still be kind, caring, and ego-free with your team.

Scientists regularly probe beyond what they can currently explain, hoping to extend the limits of explain-ability. As Carse reminds us, there are other forms of writing better suited to some of these unknown domains: “Explanations settle issues, showing that matters must end as they have. Narratives raise issues, showing that matters do not end as they must but as they do. Explanation sets the need for further inquiry aside; narrative invites us to rethink what we thought we knew” (Carse, 1987). In its infinite game play, science goes beyond explanation and steps into narrative.

Background: descriptions of hyper-rationality in the state (and the academy) flow through recent “postmodern” social theories — and discussions about postmodern theories — in the late 20th Century (Harvey, 1989; Bhabha, 1990; Best, 1991; Best and Kellner, 1997). Michel Foucault’s lectures in the late 1970s (Foucault, 2008) are a fountain of these descriptions. As an open scientist, you can make a quick note that you are not alone in seeking a better way to build teams, share knowledge, and collaborate with your peers. You knew this without ever reading Foucault.

References

Best, Steven. Postmodern Theory: Critical Interrogations. Macmillan International Higher Education, 1991.

Best, Steven, and Douglas Kellner. The Postmodern Turn. Guilford Press, 1997.

Bhabha, Homi K, and others. DissemiNation: Time, Narrative, and the Margins of the Modern Nation. na, 1990.

Binswanger, Mathias. “How Nonsense Became Excellence: Forcing Professors to Publish.” In Incentives and Performance, edited by Isabell M. Welpe, Jutta Wollersheim, Stefanie Ringelhan, and Margit Osterloh, 19–32. Cham: Springer International Publishing, 2015. https://doi.org/10.1007/978-3-319-09785-5_2.

Caron, Bruce. “Serious Games and the Study of Society,” 2017. https://doi.org/10.6084/m9.figshare.3206233.v2.

Carse, James P. Finite and Infinite Games. Ballantine Books, 1987.

Casadevall, Arturo, and Ferric C Fang. Reforming Science: Methodological and Cultural Reforms. Am Soc Microbiol, 2012.

Foucault, Michel, Arnold I Davidson, and Graham Burchell. The Birth of Biopolitics: Lectures at the Collège de France, 1978–1979. Springer, 2008.

Frith, Uta. “Fast Lane to Slow Science.” Trends in Cognitive Sciences, November 2019, S1364661319302426. https://doi.org/10.1016/j.tics.2019.10.007.

Gleick, James. The Information: A History, a Theory, a Flood. 1st ed. New York: Pantheon Books, 2011.

Krumrei-Mancuso, Elizabeth J., Megan C. Haggard, Jordan P. LaBouff, and Wade C. Rowatt. “Links between Intellectual Humility and Acquiring Knowledge.” The Journal of Positive Psychology, February 14, 2019, 1–16. https://doi.org/10.1080/17439760.2019.1579359.

Laloux, Frederic. Reinventing Organizations: A Guide to Creating Organizations Inspired by the next Stage in Human Consciousness. Nelson Parker, 2014.

McCarthy, Michael. The Moth Snowstorm: Nature and Joy. New York Review of Books, 2015.

McPhetres, Jonathon. “Oh, the Things You Don’t Know: Awe Promotes Awareness of Knowledge Gaps and Science Interest.” Cognition and Emotion, February 27, 2019, 1–17. https://doi.org/10.1080/02699931.2019.1585331.

Mountz, Alison, Anne Bonds, Becky Mansfield, Jenna Loyd, Jennifer Hyndman, Margaret Walton-Roberts, Ranu Basu, et al. “For Slow Scholarship: A Feminist Politics of Resistance through Collective Action in the Neoliberal University.” ACME: An International E-Journal for Critical Geographies 14, no. 4 (2015).

Rowland, Stephen. “Collegiality and Intellectual Love.” British Journal of Sociology of Education 29, no. 3 (May 2008): 353–60. https://doi.org/10.1080/01425690801966493.

Thomas, Douglas, and John Seely Brown. “The Play of Imagination: Extending the Literary Mind.” Games and Culture 2, no. 2 (April 2007): 149–72. https://doi.org/10.1177/1555412007299458.

The Onlyness of the Career Open Scientist

Photo Credit: Denise Krebs on Flickr. CC by 2.0

“Through the power of onlyness, an individual conceives an idea born of his narrative, nurtures it with the help of a community that embraces it, and, through shared action, makes the idea powerful enough to dent the world” (Merchant, 2017)

PLEASE NOTE: This is a draft of a bit of the Open Scientist Handbook. There are references/links to other parts of this work-in-progress that do not link here in this blog. Sorry. But you can also see what the Handbook will be offering soon.

When we look ahead at some near-future, open-science-based academy, we can point to a new science workplace solidly anchored into its own logic, with internal values that reveal its core practices. Each open organization operationalizes these values locally.

Open science is aspirational because science is hopeful: it aspires to add significant new knowledge to human understanding. The open-science movement started with open access to research results. This struggle continues. The current pandemic may accelerate this process. Next, open science needs to move to implement cultural practices that enable Demand Sharing and Fierce Equality at all levels and organizations. Certain common notions about academy practices — certain notions inherited from decades of science infested by toxic cultural habits and perverse incentives — will need to be interrogated as open science looks to open cultural practices to shape how it changes in the future. Let’s examine some of these practices.

On Onlyness

But first. The notion of, and the term “onlyness,” is from Nilofer Merchant (2017), an entrepreneur/business consultant (See also: <https://nilofermerchant.com/>; Accessed May 12, 2020). Merchant penned this term to highlight how the quality of ideas in any group springs from the distinct contribution that each person can bring into conversation, when they speak from the totality of their own knowing and being (See: Knowing and conversation). She then outlines how to optimize for this potential. Most teams and organizations underplay, or worse, prohibit, this potential, asking team members to be flexible generalists and leave their individual genius at home. They ask their members/employees to “fit in” instead inviting them to belong on their own terms.

By locating “diversity” and “inclusion” in the distinct features of each individual, Merchant re-places the standard arguments for these values within teams and organizations. No tokenism permitted here. Instead, we find a keen respect for the distinct biographies of learning and knowing carried by each person in their whole being. As Merchant (2017) notes; “To claim yourself as whole is to assert your own value — not because everything about you is perfect but because it is all perfectly yours. This acceptance of your full self is nonnegotiable in claiming the power of onlyness. If you can’t value what you alone have to offer, no one else can either.”

Onlyness belongs to every individual to the extent they make a claim about it. It is not exclusive or elite; not just a property of egoistic narcissists. It does not automatically lead to assholish behaviors. It is not acquired from membership in a population cohort or a generation, even though it is socially attuned. It is informed throughout your biography, and includes what you alone can bring to your family, your society, and the planet. Einstein’s housekeeper had as much onlyness as did Einstein, only Einstein managed to explore and mine his to the advantage of his ability for creative insight.

Very much in line with recent theories of organizational knowledge management (See: Demand sharing and the power of pull), onlyness powers innovation and creativity within teams and projects by surfacing insights across vital conversations. This also amplifies the value of networks over hierarchies. No more deference to the highest paid person in the room. Each team member has a contribution to make to this conversation. Are you looking for better conversations (of course you are), then help each person explore and claim their onlyness.

Onlyness in learning

There is no textbook sufficient to map the individual’s journey into science. There is no common, model individual open scientist: no career best practice, no business-school recipe for success can identify which scientist will excel in their research endeavor. There is no “mold” for an open scientist. Like a concert violinist, a scientist must master techniques and become proficient in their practice and precise in their methods. But that’s more like saying they’ve stopped being children and are now adults. This is the admission price to enter the “knowledge club” (Accessed May 18, 2020) of science. This alone is not what drives their individual capacity for science. It’s their launchpad, not their fuel. You can teach methods and you can learn content. That gets you to the door of science. To open it, you need to apply your onlyness.

Onlyness here means deep and broad individuality and intellectual curiosity: open scientists are deep into their own specific passion and love for some aspect of science, and their own corner of the unknown in the infinite game of science (See: Open Science and the Infinite Game). Anyone who has completed a dissertation knows the onlyness — and also the loneliness — of understanding something deeper than their books, better than their advisors, and newer than anyone else. Open scientists are also broad enough in their sense of how science works and in the landscape of methods and literature to see the larger picture of open science practice shared in their discipline and beyond.

Onlyness is the reason why scientists can uncover astonishing new insights. By “scientists” here, we mean all students of science, all members of a science team (data nerds, technical specialists, grad students, and principle investigators), in fact, all people on the planet who find that their curiosity — and their own life-to-right-now — has moved them to a distinct point of understanding: “You’re standing in a spot in the world that only you stand in, a function of your history and experiences, visions, and hopes. From this spot where only you stand, you offer a distinct point of view, novel insights, and even groundbreaking ideas. Now that you can grow and realize those ideas through the power of networks, you have a new lever to move the world” (Merchant, 2017). Onlyness is why your dissertation nearly drove you insane, since it required you to dive deep into a personal journey of discovery that now means you know more — and you know differently — from anyone else on the planet.

If professional scientists act similarly, this similarity comes from the shared depth of their appreciation for the “role of ignorance and the importance of uncertainty” in science (See: Brain Pickings; Accessed May 5, 2020). Rather like we all are in the current situation (now being May of 2020), scientists are, and have always been, alone, even when together.

Onlyness and institutional fierce equality

Institutional prestige is a profound drag on the potential for networked science. If your administration has a plan to “win” the college ratings game, this plan will only make doing science harder. It makes being a scientist less rewarding. Playing finite games of chasing arbitrary metrics or bullshit prestige drags scientists away from the infinite game play of actually doing science. In a world where Science happens elsewhere the first thing your campus can do is become more attached to all the academy “elsewheres” that can amplify your in-house efforts. The best thing your campus can do is to became that really attractive “elsewhere” to which others want to attach themselves. This means opening up to demand sharing. Once science gets funded across a broad spectrum of institutions and across the globe, online collaboratives will form, and work together, and create new knowing without regard to game-able institutional rankings. The entire academy will become more nimble, creativity will quicken, and good work will find its rewards outside of current reputation schemes.

“One will weave the canvas; another will fell a tree by the light of his ax. Yet another will forge nails, and there will be others who observe the stars to learn how to navigate. And yet all will be as one. Building a boat isn’t about weaving canvas, forging nails, or reading the sky. It’s about giving a shared taste for the sea, by the light of which you will see nothing contradictory but rather a community of love” (Saint-Exupéry, 1948; translation: <https://quoteinvestigator.com/2015/08/25/sea/>; Accessed May 11, 2020).

The future of open science will be much more distributed and democratic. Open scientists work wherever their research and teaching acumen is needed and supported. The perverse lure of bullshit-prestige institutions disappears as great work emerges from highly diverse teams in hundreds of institutions and locales across the planet, and along the internet. Instead of boasting of their employment at some famous university or lab, open scientists and their in-house and online teams are deep into the infinite game wherever they are employed. They shape the culture of their teams, bending this toward fierce equality and demand sharing. Their combined onlynesses serves to push the team effort beyond what any one of them might do. They fill open repositories with new data and findings. They care for their work together, and for each other as people. They celebrate (Celebrate open science) their team culture. A great team in a sad organization with a toxic culture works better than a sad team in a great organization.

Onlyness against neoliberal organizational metrics

The notion that a university can increase managerial control over research practices using performance-based funding schemes, and so to capture year-by-year productivity gains, has been tried in various places on the globe. But the practice of top-down, goal-driven, productivity management translates poorly from the commercial world (where this is also failing) into the academy. Metrics applied in this manner are highly susceptible to Goodhart’s law, and subsequent gaming attempts. The best incentives for better science are those goods internal to the professional practices of doing science. The best way to improve on these is to support governance practices that open up more avenues for sharing and knowing.

There is an authentic “meritocracy,” here, not the artificial sort claimed by prestigious organizations. A fluid, dynamic, emergent shared sense of where new knowing is being forged. In the interconnected intellectual rooms of online science communities, the acceleration of knowing and discovery through access to open shared resources, active, global collaborations, and diverse team-building assembles shared intelligence to solve wicked problems. There is no organizational strategic plan, no business model, no tactical hiring that can match open innovation collaborative that push the boundaries and change the rules of their infinite games together. The merit belongs to the team, and to the work. What the scientists get is the joy and wonder of playing an infinite game that also pays a salary.

Open science optimizes resources when onlyness gets support across organizations

Doing open science gets a boost when the culture of open science is shared and celebrated at the top level of academy institutions — whether its a college, a university, a learned society, or a science agency. Under these circumstances, institutional values and their shared meanings cascade down across all departments, labs, and teams. With solid, top-level institutional support, teams build their own shared mini-cultures to encourage caring and rigor.

The cultural project of open science is actually quite small. As much as open science is just “science done right” and a “return to former science norms,” the professed culture of most science organizations really only needs to be rearticulated for open science use, and celebrated as an active, reflexive cultural layer (See above). Goals are left to teams to identify and activate for themselves.

All biographies of “notable scientists” spend a great amount of their content describing the onlyness of these individuals (without calling it that). Every “genius” you read about is someone who managed to tap into their onlyness and find insights into the infinite game (which is commonly referred to as a “serendipitous” event). Every one around them — these individuals are nearly always surrounded by colleagues — contributed to these conversations. They need to noted too.

Science organizations create prizes that fail to capture the onlynesses of teams and collaboratives

No scientist has ever refused a Nobel Prize. (NOTE: Two people have declined this. Jean-Paul Sartre did, because he was Sartre. And, Le Duc Tho did, because his award was shared with Henry Kissinger, who supported bombing Hanoi during Christmas.) Learned societies and professional academic groups offer a wide range of honors that scientists gladly accept (usually along with travel support to a meeting they would like to attend). Other honors come directly from universities or funding agencies. All of these honors fatten résumés and grease promotion portfolios around the planet.

Scientists crave the economic support they need to do the work they love. If they can translate honors into cash, they will do so. And yet, should these particular honors stop being awarded, there is little to indicate that science would be less rewarding or less able to track the value of science work. Open science offers to expand opportunities to find and use great science. New methods of acknowledging the work of scientists and teams, and also the provenance of research can replace or enhance how scientists get connected to each other through their work.

Great work in open science can be found anywhere on the planet, and also within any team working in an open-science organization, small or large. The gifts of new knowledge are freely shared, but they also obligate others to pay attention. applaud their value, and scorn those who seek attention for their own finite game (See: Gifting and Reciprocity). This is central to the culture of demand sharing. Recognize the work. Applaud the teams, the history, and the ideas. Show appreciation for how this knowledge is shared, without needing to pin this discovery on an individual scientist.

You can help your students grow their onlyness too

Growing and tapping into your onlyness is not just a trait that the best open scientists share, it’s a trait that open science needs to support, to grow, and to reward. Open science is the common work of millions of un-common individuals. The education of an open scientist requires a healthy dose of infinite-game training, the unleashing of purpose and imagination, and courage and caring in service of collective knowing. In the end, it is the game that becomes the teacher, and every scientist plays this alone, even within their team. Each scientist contributes the difference they have cultivated in their own insights to the collective knowing of their team.

To help your students develop their onlyness requires that you promote in them the courage to be essentially different from those around them, and also the honesty and humility to recognize the onlyness of others. Mainly you do this by working on your own onlyness and showing how this matters. Share conversations with them that provoke responses only they can provide. Be open to learn from their knowing.

Several authors in the past decades — from Foucault and Illich to Robinson and Godin — have pointed out that factory-style schooling diminishes onlyness (without calling it thus) in favor of standardized understandings and personal disempowerment. Open science will need to also work on the cultures of learning and teaching science. Like practical wisdom (See: The practical wisdom of doing science), onlyness needs to be exercised for it to grow.

Merchant’s work on onlyness was designed to help companies become more creative and innovative through the collective conversations of their employees, powered by an organizational culture that welcomed each of them to belong to these conversations in their wholeness. What she offers to businesses holds true for the academy, and most particularly in the academy, where onlyness powers great science through networked collaborations.

References:

Merchant, Nilofer. The Power of Onlyness: Make Your Wild Ideas Mighty Enough to Dent the World. New York, New York: Viking, 2017.

Knowing and conversation in the academy

“Innovations in how we conduct conversations should be treated as art” (Schein, 2013).

Knowing

PLEASE NOTE: This is a draft of a bit of the Open Scientist Handbook. There are references/links to other parts of this work-in-progress that do not link here in this blog. Sorry. But you can also see what the Handbook will be offering soon.

First we turn to look at “knowing,” which is a practice intrinsic to scientific innovation and creativity. “Knowing,” as it is used here, has its own literature in the business-management world. Like “culture,” knowing is always shared. Elsewhere we learned about celebrations of your open-science culture (Celebrate open science). Here we will look at what Isaac Asimov called “cerebration sessions”: events planned to encourage the “folly of creativity,” in small, informal groups. These events trigger (when successful) shared knowing. Note: Asimov also noted that the subsequent written outputs for these sessions are incidental. What matters is the content of conversations in the room.

“Joviality, the use of first names, joking, relaxed kidding are, I think, of the essence — not in themselves, but because they encourage a willingness to be involved in the folly of creativeness….
I would suggest that members at a cerebration session be given sinecure tasks to do — short reports to write, or summaries of their conclusions, or brief answers to suggested problems — and be paid for that, the payment being the fee that would ordinarily be paid for the cerebration session. The cerebration session would then be officially unpaid-for and that, too, would allow considerable relaxation” (Issac Asimov, 2014: MIT Technology Review; Retrieved March 8, 2020).

You already know knowing, you just don’t know it yet

The recent work of John Seely Brown and others, coming out of organizational knowledge theories in the mid 1990s (See: Boland Jr. and Tankasi, 1995), has added (or recovered) a cultural angle on knowledge management which includes not only knowledge, but knowing: because “the interplay between knowledge and knowing can generate new knowledge and new ways of knowing” (Cook and Brown, 1999). Instead of organizations stewarding an inventory of knowledge objects, what they need to do is open up contexts and spaces: events for knowing (Thomas and Brown, 2011).

“In this way, conversation affords more than an exchange in which the net sum of knowledge remains the same; it dynamically affords a generative dance within which the creation of new knowledge and new ways of using knowledge is possible.
Engaging in such conversation is a practice that does epistemic work; it is a form of knowing. Knowing entails the use of knowledge as a tool in the interaction with the world. This interaction, in turn, is a bridging, a linking, of knowledge and knowing…[Which] makes possible the generative dance, which is the source of innovation. The generative dance, within the doing of work, constitutes the ability to generate new knowledge and new ways of using knowledge — which knowledge alone cannot do. And which the organizations of the future cannot afford to neglect” (Cook and Brown, 1999).

These events for knowing are where organizations do their “sense-making” activities, and where scientists collaborate in conversation to solve — to make sense of — the emergent complexities of nature. Scientists use knowing practices every time a new experiment is made. Each time the scientist creates a new test to interrogate a piece of unknown nature, she hopes to distill a bit of new knowledge and a ray of understanding that might lead to new knowing. They share this knowing in conversations with their colleagues.

While the “official record” for a new discovery might be a published paper, open science works to accelerate sharing by promoting preprints that open up immediate opportunities for scientific conversations across the internet.

Conversations power scientific discovery

“[N]etworked markets get smart fast. Metcalfe’s Law, a famous axiom of the computer industry, states that the value of a network increases as the square of the number of users connected to it — connections multiply value exponentially. This is also true for conversations on networked markets. In fact, as the network gets larger it also gets smarter. The Cluetrain Corollary: the level of knowledge on a network increases as the square of the number of users times the volume of conversation. So, in market conversations, it is far easier to learn the truth about the products being pumped, about the promises being made, and about the people making those promises. Networked markets are not only smart markets, but they’re also equipped to get much smarter, much faster, than business-as-usual” (Levine, et al, 2009 [1999]. Emphasis added.)

The very first one of the ninety-five theses of the Cluetrain Manifesto (ibid) says this: Markets are Conversations. The “markets” for research knowledge in open science connect to the emergent abundance of research artifacts in repositories across the globe. But the knowledge that powers discovery right now lives only in the conversations available across networks of scholars. Buckheit and Donoho (1995) make the point that scientific articles rarely hold the scholarship they claim to convey: rather they are “merely advertising of the scholarship.”

The solution is two-fold: better ways of publishing results that reproduce more of the method, data, software, and ideas (open science looks to go “beyond the PDF”); and more conversations quicker and across a wider range of internet-enabled media, including online direct conversations among peer-to-peer networks. As we learned above (Science happens elsewhere), these networks create virtual “rooms” that are smarter than any of their inhabitants. Following the Cluetrain Corollary, we can assert the following:

“The level and quality of current knowing in any science discipline increases as the square of the number of scientists times the amount of available conversation.”

Through Demand Sharing and Fierce Equality, open science resets the norms for research conversations across the planet. Today, virtual science organizations can be easily bootstrapped through platform cooperatives to support active collaborations across institutions and continents.

Extra Credit: For those of you who follow recent French philosophy, these knowing events are the center of the process from which truths emerge in the philosophy of Alain Badiou. “[A] truth is sparked by an event and spreads like a flame fanned by the breath of a subjective effort that remains forever incomplete. For truth is not a matter of theory but is a ‘practical question’ first and foremost: it is something that occurs, a point of excess, an evental exception, ‘a process from which something new emerges’…” (Bensaïd, 2004; Retrieved March 10, 2020).

Of course you do not need to read French philosophy to understand what Asimov and Badiou are telling you: one great conversation (perhaps over beer at a conference, or online on a teleconference) with a colleague about the intersections of your research can be more valuable — can spark more truths about your object of study — than any article or book in your library.

References

Boland Jr, Richard J, and Ramkrishnan V Tenkasi. “Perspective Making and Perspective Taking in Communities of Knowing.” Organization Science 6, no. 4 (1995): 350–372.

Buckheit, Jonathan B, and David L Donoho. “Wavelab and Reproducible Research.” In Wavelets and Statistics, 55–81. Springer, 1995.

Cook, D.N., and John Seely Brown. “Bridging Epistemologies: The Generative Dance between Organizational Knowledge and Organizational Knowing.” Organization Science 10, no. 4 (1999): 381–400. http://www.jstor.org/stable/2640362.

Levine, Rick, Christopher Locke, Doc Searls, and David Weinberger. The Cluetrain Manifesto. Basic books, 2009.

Schein, Edgar H. Humble Inquiry: The Gentle Art of Asking Instead of Telling. Berrett-Koehler Publishers, 2013.

Thomas, Douglas, and John Seely Brown. A New Culture of Learning: Cultivating the Imagination for a World of Constant Change. Vol. 219. CreateSpace Lexington, KY, 2011.

Demand sharing unleashes the “power of pull” for your science research

“In a closed society where everybody’s guilty, the only crime is getting caught. In a world of thieves, the only final sin is stupidity” (Thompson, 1971).

“Pull allows each of us to find and access people and resources when we need them, while attracting to us the people and resources that are relevant and valuable, even if we were not even aware before that they existed” (Hagel 2010; Retrieved February 26, 2020).

Credit: Rachel Smith on Flickr. John Seely Brown talk

“Sharing” gone massively wrong: academic publishing

PLEASE NOTE: This is a draft of a bit of the Open Scientist Handbook. There are references/links to other parts of this work-in-progress that do not link here in this blog. Sorry. But you can also see what the Handbook will be offering soon.

Why is Demand Sharing so important to open scientists like you? We are going to explore this question here. Let’s begin with the poster-child for research-sharing-gone-wrong: “for-profit science publishing.” At the same time you’ve been perfecting your demand-sharing techniques in the classroom, you’ve surrendered your research to one of the strangest marketplace transactions in modern times.

Academics give their research to publishers; give the publishers their copyrights; and also donate an additional sixty-eight million hours a year (Nature News Sept 7, 2018: <https://www.nature.com/articles/d41586-018-06602-y>) reviewing the work of others for free. Academic libraries must each pony up millions of dollars a year to keep their subscriptions current. The public gets dinged thirty to forty dollars (US) a pop just to read a single article. The process of selecting articles often leads to months or years between discovery and publication, and warps the output toward positive (and false-positive) “sexy science” results. The remainder of research results go unpublished. “Economists may not have terms adequate to describe a market as dysfunctional as the one operating for academic publishing” Neff (2020; Retrieved February 26, 2020) notes.

How did this happen?

Potts (et al, 2017) points to a failure of the publishing capacity of academic societies to scale with the blossoming of science output after World War II:

“The wartime and post-war expansion of public research funding and consequent expansion and globalisation of research communities were soon exploited by an entrepreneur-led proliferation of increasingly specialised journals, following the lead of Robert Maxwell’s Pergamon Press (Buranyi, 2017; retrieved February 25, 2020). The small society presses, struggling to cope with growing scale, were supported and then largely supplanted by the ‘Big 5’ commercial presses: Elsevier (which acquired Pergamon in 1991), Wiley, Springer, Taylor & Francis and Sage. These newly-empowered players brought an industrial approach to the publication and dissemination process, for the first time realising the benefits that these specialised capital and skills could provide by operating at a scale that was unprecedented to that date. The successful publishers grew (and consolidated to grow further) alongside a pre-Cambrian explosion and specialisation of journals to create the modern landscape in which the majority of journals is owned, controlled or at least produced by a handful of globalised companies.”

A committee at the National Academies of Sciences (2018) offers additional historical information:

The 1990s brought a wave of consolidation among scientific publishers, as Netherlands- based Elsevier acquired Pergamon, leaving it in control of over 1,000 journals (Buranyi, 2017 [ibid]). Further increases in subscription prices and the advent of “big deal” agreements between publishers and libraries followed in the late 1990s. Under these agreements, publishers agree to provide online access to a bundle of their journals, including all back issues, priced at a discount to the sum of the individual journal subscriptions (Bergstrom et al., 2014). Despite paying lower per journal prices, total outlays by libraries increased to the point where this has been called the “serials crisis” (Panitch and Michalak, 2005[white paper is no longer online]). In 2015, Larivière et al. found that the five most prolific publishers, including Reed-Elsevier, Taylor & Francis, Wiley-Blackwell, Springer, and Sage, control over one-half of all the scientific journal market, and that the profit margins of these companies have been in the range of 25 to 40 percent in recent years (Larivière et al., 2015). According to one economist who studies the industry, this situation “demonstrates a lack of competitive pressure in this industry, leading to so high profit levels of the leading publishers that they have not yet felt a strong need to change the way they operate” (Björk, 2017a).

Both of these accounts point to older, established cultural practices based on demand sharing within the academy being disrupted and displaced by marketplace profit seeking. By the end of the Nineteenth Century, the academy had taken control of its own research sharing practice through the advent of hundreds of member-run professional societies — each with their own publishing effort. Within these societies, members freely gave up their research for review and publication. University presses added their capacity as well.

In demand sharing, a “demand” is a culturally-grounded request

As academic institutions, the societies and universities demanded research finding from their members, in much the same fashion that students can demand knowledge from their professor in the lecture hall. Sharing is both expected and normative. Merton (1973) noted that:

“The institutional conception of science as part of the public domain is linked with the imperative for communication of findings. Secrecy is the antithesis of this norm; full and open communication its enactment. The pressure for diffusion of results is reenforced by the institutional goal of advancing the boundaries of knowledge and by the incentive of recognition which is, of course, contingent upon publication.”

Societies provided both the means of building the shared, public, academic corpus, and the platform for recognition. Yet this individual recognition was also tempered with the larger sense that all knowledge is interlinked and historically accumulated. Merton (ibid) writes: “The communal character of science is further reflected in the recognition by scientists of their dependence upon a cultural heritage to which they lay no differential claims.”

Demand sharing on the open web

Open science efforts in the last twenty years have been centrally focused on refactoring the means of academic publication to take advantage of the opportunities provided by the internet, and to remove the foreign, marketplace, logic in order to reassert the “communal character” of science publishing, grounded in the logic of demand sharing (although they haven’t called it that). Unlinking the act of giving research results back to the science community — which has long been a community norm — from the more recent practice of giving away research results to the marketplace — to own from there forward — restores these results as internal “gifts” within a community guided by demand sharing. There is more. At the same time that open science releases the academy from its recent marketplace bondage (freeing up financial resources in the process), a new, networked marketplace for “ideas” in and out of the academy is also challenging the notion of organizational knowledge ownership, in favor of what Hagel (et al, 2012) calls the “power of pull.”

Large corporations, fledgling start ups, and, yes, even ivory tower universities can access an explosion of shared knowledge and lateral learning when they decide to pull information from global networks. “Institutions can significantly amplify the power of pull, making it far easier to connect with a broader range of people and resources and to learn faster from each other than we ever could in the absence of institutions. We must therefore reclaim our institutions — whether from the inside of existing ones or by creating a new generation of our own.” Open science works to reclaim the academy as learning hubs that can pull information from academy commons resources across the planet.

Goldman and Gabriel (2005) observed that “innovation happens elsewhere”; that the crowd- and network effects of open communities could assemble more talent, a greater variety of knowledge, and effective collective intelligence(s) well beyond those that any company/university/lab could afford to assemble internally. Their arguments were informed by Bill Joy, a co-founder of Sun Microsystems, who wrote in the 1990s: “no matter who you are, most of the smartest people work for someone else” (Wikipedia). This is known in management theory as Joy’s law. And it holds ever more strongly for your university, your agency, or your laboratory.

Many corporate management experts point out that openly sharing ideas across corporations (Golden and Gabriel, 2005; Leadbetter, 2005 <https://www.ted.com/talks/charles_leadbeater_on_innovation?> Retrieved April 21, 2019), and gathering ideas from customers and external sources (Bissola et al, 2017), will lead to better, faster corporate innovation. In fact, you can say, with some authority, that the future of innovation in the academy will require the logic of demand sharing.

The marketplace logic of intellectual property ownership and practice of demand sharing for knowledge are antithetical. They do not play well together. For-profit efforts to include “open practices” invariably lead to open-washing, and the final closure of collected resources as intellectual property (Neylon, 2017). Open for them means “free to acquire” and mainly serves to lower their resource costs. Demand sharing is an older practice, older in the academy, and still older in the species, being a primary form of cultural practice over thousands of years. It privileges internal goods over the external goods and incentives of the market.

To understand this further, jump to (See: Deep dive: Gifting and Reciprocity), where you can explore how each act of demand sharing builds a social bond that can be used to stimulate other occasions of sharing. The academy also needs to break completely from seeking to own intellectual property inside individual organizations (Deep Dive: Against Patents in the Academy) in favor of academy-wide ownership supporting a shared resource commons for intellectual property. Current work on the creation of “Civic Trusts” offers a productive way forward for the academy (See: The Civic Trust; Retrieved February 26, 2020).

References

Bergstrom, Theodore C, Paul N Courant, R Preston McAfee, and Michael A Williams. “Evaluating Big Deal Journal Bundles.” Proceedings of the National Academy of Sciences 111, no. 26 (2014): 9425–9430.

Bissola, Rita, Barbara Imperatori, and Alfredo Biffi. “A Rhizomatic Learning Process to Create Collective Knowledge in Entrepreneurship Education: Open Innovation and Collaboration beyond Boundaries.” Management Learning 48, no. 2 (April 2017): 206–26. https://doi.org/10.1177/1350507616672735.

Björk, B.C. “Scholarly Journal Publishing in Transition — from Restricted to Open Access.” Electronic Markets 2, no. 101–109 (2017).

Goldman, Ron, and Richard P. Gabriel. Innovation Happens Elsewhere: Open Source as Business Strategy. Morgan Kaufmann, 2005.

Hagel, John, John Seely Brown, and Lang Davison. The Power of Pull: How Small Moves, Smartly Made, Can Set Big Things in Motion. Basic Books, 2012.

Larivière, Vincent, Stefanie Haustein, and Philippe Mongeon. “The Oligopoly of Academic Publishers in the Digital Era.” Edited by Wolfgang Glanzel. PLOS ONE 10, no. 6 (June 10, 2015): e0127502. https://doi.org/10.1371/journal.pone.0127502.

Merton, Robert K. The Sociology of Science: Theoretical and Empirical Investigations. University of Chicago press, 1973.

National Academies of Sciences, Engineering, and Medicine (U.S.). Open Science by Design: Realizing a Vision for 21st Century Research. A Consensus Study Report. Washington, DC: The National Academies Press, 2018.

Neylon, Cameron. “Openness in Scholarship: A Return to Core Values?” Stand Alone, 2017, 6–17. https://doi.org/10.3233/978-1-61499-769-6-6.

Potts, J., J. Hartley, L. Montgomery, C. Neylon, and E. Rennie. “A Journal Is a Club: A New Economic Model for Scholarly Publishing.” Prometheus 35, no. 1 (2017): 75–92. https://doi.org/DOI: 10.1080/08109028.2017.1386949.

Thompson, Hunter S. Fear and Loathing in Las Vegas; a Savage Journey to the Heart of the American Dream. Random House, 1972.

Science happens elsewhere

“The smartest person in the room is the room itself: the network that joins the people and ideas in the room, and connects to those outside of it” (Weinberger, 2011).

Elsewhere: where the adjacent possible opens up to the power of pull (Hubble Telescope image)

PLEASE NOTE: This is a draft of a bit of the Open Scientist Handbook. There are references/links to other parts of this work-in-progress that do not link here in this blog. Sorry. But you can also see what the Handbook will be offering soon.

Goldman and Gabriel (2005) penned to phrase: “Innovation happens elsewhere” to capture the value of open-source software communities. In the academy, it doesn’t matter if you are at Oxford or in Oxnard, almost everything you need to know to make the next step in your research is also being considered at this moment: somewhere else.

In the academy, this “beyond” is a global intellectual commons now becoming abundant with open data and accessible — and reproducible (Crick, et al, 2015) — research results. Using online peer production methods (Benkler, 2016), the academy can optimize the value of this commons for innovation, knowledge, and growth. “[P]eer production practices [are] highly adept at learning and experimentation, innovation, and adaptation in rapidly changing, persistently uncertain and complex environments” (ibid).

The only competition your academy organization has is within itself. As other institutions — including new virtual science organizations — work to continuously improve on their work, your team needs to focus on leveraging the learning engine of double-loop governance to get better than your yesterday. In the infinite game of science, winning means accelerating your team’s learning and sharing capacity through what (Hagel and Brown, 2011) call a “creation net” for open innovation. Standing still is not an option when the research world is exploding somewhere else. This “explosion of creativity is taking over more and more of our world. Everyone involved in it is at the same time a producer and a consumer, a worker and a manager…. Progress in most academic disciplines now seems to move at the speed of ‘instantaneous,’ with discoveries building atop one another at a dizzying pace” (Ito and Howe, 2016).

Creation networks: open science’s network effect

A creation network is enabled by a certain quality of learning within social interactions, a greater quantity of information flows (and/or a greater attention to these), an availability of interpersonal trust (based on demonstrated skills and commitment), and an environment of reflexive involvement: all benefits of belonging to a community-led double-loop governance. “[I]nstitutions will need to become much more selective in their efforts to protect existing stocks of knowledge and much more adept in using their stocks of knowledge to contribute more actively in creation nets and to plug into promising flows of knowledge” (Hagel and Brown, 2008). Data-intensive science (Hey, et al, 2009) in a whitewater world of global research demands a nimble governance for its teams, labs, networks, societies, universities, and agencies.

Know enough to know enough

When your academy organization looks to innovate — or when your personal research is looking to find the right question to ask — in a world where multiple/large data/information inputs, and international science discoveries are coming on line, how can you stay ahead of this emergent complexity? One way to look at this problem is through Ashby’s principle/law of requisite variety, coming from cybernetic management. Ashby’s law notes that unless the control system has at least the variety of the environment it controls, it will fail; which actually means that some part of the environment will be controlled elsewhere.

You need to join the science elsewhere. Elsewhere is where other science teams are now playing the infinite game in collaboration, asking the questions that their networked teamwork generates. Elsewhere there are flows of information being shared across the planet. That is a great reason for new creation networks in the academy: for open science sharing across the academy.

Elsewhere is where innovation happens; because unless you can corral the inherent variety of the problem you face, it will be too complex for your team to innovate a response. If you are not engaged with the open-science elsewhere that is opening up today, your team will suffer. You can either go out and hire a bigger team (good luck talking your chancellor or the NSF into that), or you can borrow enough requisite variety just long enough to bring your own team up to speed by starting up or hooking into an online creation network. You can join the sharing economy, play the infinite game, and get better at it every day. Or you can rest on your (bullshit) reputation and keep on thinking the world will come to you.

When members are given license to form working teams across organizations, they also expand the extent of where their research adjacent possible is found; creative interactions and new knowledge become predictable outcomes. The larger the room, the smarter it gets. Find the room to nurture your research.

When the adjacent possible is a globally available

The “adjacent possible” is a notion that comes from biological theories of coherent change. It describes how the surrounding environment tucked between stasis and chaos provides a resource of available change. The adjacent possible enables, and almost guarantees, certain changes (while ruling out others) out of potentially infinite play of innovation.

“Biospheres, on average, may enter their adjacent possible as rapidly as they can sustain; so too may econospheres. … [T]he hoped-for fourth law of thermodynamics for such self-constructing systems will be that they tend to maximize their dimensionality, the number of types of events that can happen next” (Kauffman, 2000). Every new piece of information, each new proto-fact, expands the horizon of the infinite game of science (See: Learning to play the infinite game). The more scientists that add this new fact to their knowledge, the larger their mutual adjacent possible becomes.

Steven Johnson [Retrieved 1/15/2020], uses the metaphor of “liquid” to describe the optimal network environment to enable innovation (Johnson, 2011). “Solid” networks are too stiff to pivot toward “the adjacent possible” where new ideas sprout. “Gas” networks are too chaotic. “In a solid, the opposite happens: the patterns have stability, but they are incapable of change. But a liquid network creates a more promising environment for the system to explore the adjacent possible.” (Ibid).

More specifically, liquid networks — and the academy organizations that create these — enable individual researchers and teams to explore the adjacent possible; “When the first market towns emerged in Italy, they didn’t magically create some higher-level group consciousness. They simply widened the pool of minds that could come up with and share good ideas. This is not the wisdom of the crowd, but the wisdom of someone in the crowd. It’s not that the network itself is smart; it’s that the individuals get smarter because they’re connected to the network.” (Ibid). The room makes everyone smarter; these new everyones make the room smarter. You need to find/build that room. When you do, you use demand sharing to pull the information and knowledge you need right now to move ahead in your research (See: Demand sharing and the power of pull).

The liquid network is another way of talking about network diversity, the optimal mix of strong ties, weak ties, and strangers in direct communication (See: Ruef, 2002) that is a key predictor for innovation in the global elsewhere your research can call home. How do you get this home? The most reliable starting place is to build a culture of organizational learning into your organization. Double-loop governance is a durable platform on which to develop liquid networks across the academy, or in your lab or your department, and at your learned society.

References

Benkler, Yochai. “Peer Production and Cooperation.” Handbook on the Economics of the Internet 91 (2016).

Crick, Tom, Benjamin A Hall, and Samin Ishtiaq. “Reproducibility in Research: Systems, Infrastructure, Culture.” ArXiv Preprint ArXiv:1503.02388, 2015.

Goldman, Ron, and Richard P. Gabriel. Innovation Happens Elsewhere: Open Source as Business Strategy. Morgan Kaufmann, 2005.

Hagel, John, and John Seely Brown. “Creation Nets: Harnessing The Potential Of Open Innovation.” Journal of Service Science 1, no. 2 (2008): 27–40.

Hey, Anthony J. G., ed. The Fourth Paradigm: Data-Intensive Scientific Discovery. Redmond, Washington: Microsoft Research, 2009.

Ito, Joi, and Jeff Howe. Whiplash: How to Survive Our Faster Future. Grand Central Publishing, 2016.

Kauffman, Stuart. At Home in the Universe The Search for the Laws of Self-Organization and Complexity. Cary: Oxford University Press, USA, 2014.

Ruef, Martin. “Strong Ties, Weak Ties, and Islands: Structural and Cultural Predictors of Organizational Innovation.” Industrial and Corporate Change 11, no. 3 (2002): 427–449.

Weinberger, David. Too Big to Know: Rethinking Knowledge Now That the Facts Aren’t the Facts, Experts Are Everywhere, and the Smartest Person in the Room Is the Room. Basic Books, 2011.

The Congruent Scientist: Playing the infinite game builds personal wisdom

The aikidoka does not let distraction affect her kime 決め… her focus and attention. She is congruent in her form.

“Yet notoriously the cultivation of truthfulness, justice and courage will often, the world being what it contingently is, bar us from being rich or famous or powerful. Thus although we may hope that we can not only achieve the standards of excellence and the internal goods of certain practices by possessing the virtues and become rich, famous and powerful, the virtues are always a potential stumbling block to this comfortable ambition” (MacIntyre, 1984).

PLEASE NOTE: This is a draft of a bit of the Open Scientist Handbook. There are references/links to other parts of this work-in-progress that do not link here in this blog. Sorry. But you can also see what the Handbook will be offering soon.

Alasdair MacIntyre’s caveat rings true when applied to finite power games in and out of the academy. It’s the same “nice guys finish last” logic that your academic advisor may have given you; “practical” advice that many in the academy have used as an alibi against sharing their data and methods openly. Open scientists know better. This logic exposes how the external goods of the neo-liberal market are crowding out the internal goods so vital to the success of science as a practice. Nicholas Gruen (Retrieved February 21, 2020) puts it this way: “Here’s the serpent in paradise. External goods are necessary, but, at the same time, in tension with internal goods. This is an ethical tension. The risk is always that the pursuit of external goods compromises the pursuit of internal goods, and thus the excellence of the practice.”

Certainly, during the transition phase to open practices of Fierce Equality and Demand Sharing, there will still be games for external goods where the few consider themselves winners and all others as losers. The hyper-competition for scarce external goods in the academy is not going to simply disappear on its own. Today, dozens of open science endeavors have articulated alternative solution pathways for distributing external goods without supporting perverse incentives (Edwards and Roy, 2017; Bartling and Friesike, 2014). However, building alternative practices through intentional culture change takes time and effort. The open, infinite game of science treasures its abundant internal goods — including internal measures of recognition and modes of compensation — above money, fame, and glory. Something to remember when you have little of the latter.

One particular internal good in the academy happens when your work and your person become congruent. The practical wisdom you learn and apply to your research, and with your teammates, you can also use in your life with friends and family.

Background on the notion of congruence

In 1961, the psychotherapist Carl Rogers compiled three decades of papers into the book On Becoming a Person. The main frame of the book describes his client-centric approach to psychotherapy, how he arrived at this and what he learned as a practitioner, many of the articles — which read very much as blogs do today (and were unpublishable in the scientific journals for this reason). He then links this frame to other human endeavors. In particular, he looks to education and personal relations in organizations.

His main therapeutic process involves how the psychoanalyst as a person, develops her own personhood by becoming more congruent (more about this in a minute) and then uses this congruence as a communication tool to open up the client to the process of becoming more congruent. The therapist is really only someone further along the same road to “becoming a person.”

The process of becoming a person, of achieving more and wider congruence, and so having fewer and fewer defenses, brings the client to a better life, with less tension and fear, better communication with everyone, and new opportunities to explore each moment fully. For Rogers, congruence happens when one’s real self (the one we all start out with — all infants are congruent — also the one we can shape with our own skills and the virtues we learn) fully resembles one’s ideal self (the one we acquire from social interactions with others).

The lack of congruence leads to the need to defend the ideal self every time the real self behaves differently, or when people respond to the real self instead of the ideal self. The real self becomes hidden and, indeed, often unknowable; which forms the reason for therapeutic intervention. The goal of congruence is also extremely well aligned with the goal of “becoming a scientist:” congruence unlocks intellectual creativity.

Creativity in science is a self-therapeutic practice

“The mainspring of creativity appears to be the same tendency which we discover so deeply as the curative force in psychotherapy — man’s tendency to actualize himself, to become his potentialities.…This tendency may be come deeply buried under layer after layer of encrusted psychological defenses; it may be hidden behind elaborate façades which deny its existence; it is my belief however, based on my experience, that it exists in every individual, and awaits only the proper conditions to be released and expressed. It is this tendency which is the primary motivation for creativity as the organism forms new relationships to the environment in its endeavor most fully to be itself” (Rogers, 1961).

The ideal self represents the roles you acquire in order to play finite games in your life and career. For example, in your academic position, you are “The Scientist.” As Carse (1987) noted and Rogers might agree here, you have forgotten that you have the freedom to set aside your role. Quite the reverse: the role has become you. This is why you spend so much effort defending your ideal self/role, even (or especially) against your real self. How do you escape?

“[P]rogress in personal life and in group living is made in the same way, by releasing variation, freedom, creativity” (Rogers, 1961). The creativity you invest in the infinite game of science builds the capacity you can use to release your real self from the roles you play in finite games. You acquire the mindset of an infinite game player and become self-directed toward congruence. As Rogers notes:

“[T]he individual who is open to his experience, and self-directing, is harmonious, not chaotic, ingenious rather than random, as he orders his responses imaginatively toward the achievement of his own purposes. His creative actions are no more a chaotic accident than was Einstein’s development of the theory of relativity” (ibid).

Simon Sinek (2019) would add that your infinite game mindset is precisely what you need to succeed as a team member in 21st Century science.

Open science and an open you

How does the authenticity of doing science as an infinite game bleed over into your personal life? Can science really make you a “better person”? The skills you acquired to become a scientist, and the cultural practices of open science you are weaving into your work are tools you can use if you bring along the courage to seek change; “making courage part of your personal culture means you are always willing to keep making changes in your life until it is the life that you want and the life that you deserve. Courage in your life means you accept that there will be missteps — that constant and repeated change may be necessary, but that it is nothing to be ashamed of if it leads to a more fulfilling, positive outcome” (Dudley, 2018).

The intellectual tools of science, such as rigorous, reflexive curiosity, openness, and intellectual humility are available to the scientist for use in other circumstances. You can bring these skills home with you. The same kindness and humility you bring (one hopes) to your teaching and research can become an interactive style elsewhere.

On becoming an organization

“If things aren’t going right, the first response is: let’s make more rules, let’s set up a set of detailed procedures to make sure that people will do the right thing. Give teachers scripts to follow in the classroom, so even if they don’t know what they’re doing and don’t care about the welfare of our kids, as long as they follow the scripts, our kids will get educated. Give judges a list of mandatory sentences to impose for crimes, so that you don’t need to rely on judges using their judgment….Impose limits on what credit card companies can charge in interest and on what they can charge in fees. More and more rules to protect us against an indifferent, uncaring set of institutions we have to deal with” (Barry Schwartz, 2011 TED Talk<https://www.ted.com/talks/barry_schwartz_using_our_practical_wisdom/transcript>; Retrieved 02/17/2020.

In the Handbook’s section on Learning Organizations, we discovered double-loop learning/governance. Double-loop governance maps directly into congruence at the organizational level: the so-called “ideal” organization being the first loop, and the real organization being the second loop. Instead of hiding the real organization behind the idealized intentions of the founder, or top-down rules and regulations derived from an imperious CEO or provost, double-loop governance makes the real organization available to every member. Each member has the same view and purview of the rules and roles, the values and the vision of the organization, and also an obligation to make these congruent with the everyday activities of the organization.

The notion that your organization can also be a therapeutic setting where members can learn to become more congruent may seem peculiar today, where management mainly promotes rule-governed compliance. Barry Schwartz tells us to stop already with the rules and use our everyday interactions to grow social and personal virtues:

“Rules and incentives don’t tell you how to be a good friend, how to be a good parent, how to be a good spouse, or how to be a good doctor or a good lawyer or a good teacher. Rules and incentives are no substitutes for wisdom. Indeed, we argue, there is no substitute for wisdom. And so practical wisdom does not require heroic acts of self-sacrifice on the part of practitioners. In giving us the will and the skill to do the right thing — to do right by others — practical wisdom also gives us the will and the skill to do right by ourselves. (Barry Schwartz, 2011 TED Talk<https://www.ted.com/talks/barry_schwartz_using_our_practical_wisdom/transcript>; Retrieved 02/17/2020.

Remember also that organizational Knowing — the stock of sharable knowledge that defines your academic institution’s main research resource — is a series of conversations between two or more people. Knowing cannot be stored, only generated anew as each conversation leverages the prior ones. Your organization’s culture and governance sets up the circumstances at work where members can (or cannot) communicate effectively to share their insights and grow creativity. Mainly what they share is a specific, collective scientific ignorance.

“This [the shared ignorance in a scientific conversation] is knowledgeable ignorance, perceptive ignorance, insightful ignorance. It leads us to frame better questions, the first step to getting better answers. It is the most important resource we scientists have, and using it correctly is the most important thing a scientist does” (Firestein, 2012). Using open science and the infinite game, you can make your organization a place where each member can become more of a person. In return they will make your organization a better place in which to get science done.

Coda

You’ve likely met one or more congruent scientists. Someone who has engaged you in conversation at a workshop or conference. You walk away thinking, “She is so open and intellectually humble, knows so much, and asks really great questions. She must be such fun to work with.” You might have also sensed a wellspring of truthfulness, justice, and courage there. A corner of your ego might wonder what she thought of you. If you were playing the infinite game with her, and not trying to win points, she probably noticed.

You may also have visited a congruent organization (or, with great luck, you’ve ended up working in one), and come away wondering how they manage to avoid all the administrative bullshit you deal with every day. How do they sustain that level of creative interactions? How come everybody felt safe enough to say those things out loud? What does one need to do to get a job there?

In the Earth sciences, there’s a virtual organization called Earth Science Information Partners (ESIPfed.org). This is a great example of a congruent organization. A few years back, they hired an independent review organization to advise them what they could do to improve. The report came back: sorry, everyone who knows you, loves how you work right now. The reviewers were apologetic about not exposing a range of problems. ESIP has been a double-loop learning organization for two decades. It shows. Here’s an introduction to their bi-yearly gatherings.

The Open Scientist Handbook offers tools for you to become more congruent and to build congruent governance practices into your own academy home.

References

Bartling, Sönke, and Sascha Friesike, eds. Opening Science: The Evolving Guide on How the Internet Is Changing Research, Collaboration and Scholarly Publishing. Heidelberg: Springer Open, 2014.

Carse, James P. Finite and Infinite Games. Ballantine Books, 1987.

Dudley, Drew. This Is Day One: A Practical Guide to Leadership That Matters. First edition. New York: Hachette Books, 2018.

Edwards, Marc A., and Siddhartha Roy. “Academic Research in the 21st Century: Maintaining Scientific Integrity in a Climate of Perverse Incentives and Hypercompetition.” Environmental Engineering Science 34, no. 1 (January 2017): 51–61. https://doi.org/10.1089/ees.2016.0223.

Firestein, Stuart. Ignorance: How It Drives Science. New York: Oxford University Press, 2012.

MacIntyre, Alasdair C. After Virtue: A Study in Moral Theory. 2nd ed. Notre Dame, Ind: University of Notre Dame Press, 1984.

Rogers, Carl Ransom. On Becoming a Person: A Therapist’s View of Psychotherapy. Houghton Mifflin Harcourt, 1995.

Sinek, Simon. The Infinite Game. New York: Portfolio/Penguin, 2019.