“It is true that many people in science will scoff if you try to tell them about a scientific community in which ideas are treated as gifts. This has not been their experience at all. They will tell you a story about a stolen idea. So-and-so invented the famous such and such, but the man down the hall hurried out and got the patent. Or so-and-so used to discuss his research with his lab partner but then the sneaky fellow went and published the ideas without giving proper credit. He did it because he’s competitive, they say, because he needed to secure his degree, because he had to publish to get tenure — and all of this is to be expected of departmentalized science in capitalist universities dominated by contractual research for industry and the military” (Hyde 2009).
REVISED: September 1, 2020
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.
In researching the forty years of allowing publicly funded primary research results to be patented in the US, what becomes clear is that for every success story there are scores of negative outcomes. The bureaucracy that universities build to capture the “value” of research as patents (Welpe et al. 2015), the administrative burden on researchers to conform their work to the process of patent-making (Stodden 2014; Graeber 2019), the perverse career pressure to produce more patents (Edwards and Roy 2017), the downstream roadblocks for sharing the research (NAS 2018): the entire ecosystem (or egosystem) of doing patents argues against their benefits to the academy. The underlying tension between the university’s long-term mission as a wellspring of new public knowledge and the market’s desire to acquire and privatize new discoveries remains at issue here (Foray and Lissoni 2010).
The Handbook is not a primary source for arguments around patents, and will only point to some major issues and a handful of available resources on this topic. Gerald Barnett (Accessed August 31, 2020) has assembled a useful resource on the web for those interested in university patent issues. The Handbook argues that open science works best within a shared resource commons, where the neoliberal market is held apart, but likely never fully absent, for the duration. Open science and closed knowledge transfer practices do not play well together.
You might work in one of very few select sub-disciplines (usually within bio-medical or IT research) at one of the few universities where university patents have had some historical financial returns. But for the other ninety-five percent of science, and for the academy as a whole, the value of sharing research far exceeds whatever near-term monetized return might be available. Newfield (2016) summarizes the situation this way:
“The point here is not that the University of California and American research were doing badly. To the contrary, they were producing the normal market results of doing research very well, which (with rare exceptions) is to spend lots of money rather than to earn it. The market results of innovative research are, as research results, close to nil. This is as it should be. The purpose of innovative research is innovation — discovery, invention, and scientific progress. This research has great long-term and social value that could not be captured as licensing revenue or estimates of the market value of patents.
The contribution of the research university can best be appreciated in broader, postmarket terms. The research university was designed to investigate every topic of conceivable public interest, from astronomical physics to agricultural genetics and everything in between. Major commercial returns accrued to research in a fairly narrow band of fields largely found in information technology and biomedicine….”
University research results have also, historically, been “transferred” to the academy, industry, and the public through a diverse portfolio of channels (publications, workshops, conferences, etc.). Patents interfere with these other channels. “[W]idespread patenting and restrictive licensing terms may in some cases hamper, rather than promote, technology transfer from universities to industry. These policies may also obstruct the process of scientific research (Mowery et al. 2001). Foray (2004) puts it like this: “Most studies on these issues show that this evolution [toward patenting basic research] represents a real risk of irremediable alteration of modes of cooperation and sharing of knowledge in the domain of basic research. When there is nothing left but exclusive bilateral contracts between university laboratories and firms, there are forms of quasi-integration that undermine the domain of open knowledge.”
Remembering here that science is a long game, an infinite game (See: Learning to play the infinite game). The actual returns on research are mostly “postmarket” in value. Open sharing accelerates returns in the near term and compounds research value over time. Universities achieve their value proposition through a broad range of research and educational activities. The availability of market returns from patents for a small segment of university research threatens to warp the research opportunity landscape, and the normative internal incentives (including curiosity) for research (Strandberg 2005).
“In an age when ideas are central to the economy, universities will inevitably play a role in fostering growth. But should we allow commercial forces to determine the university’s educational mission and academic ideals? In higher education today corporations not only sponsor a growing amount of research — they frequently dictate the terms under which it is conducted. Professors, their image as unbiased truth-seekers notwithstanding, often own stock in the companies that fund their work. And universities themselves are exhibiting a markedly more commercial bent. Most now operate technology-licensing offices to manage their patent portfolios, often guarding their intellectual property as aggressively as any business would. Schools with limited budgets are pouring money into commercially oriented fields of research, while downsizing humanities departments and curbing expenditures on teaching” (Press and Washburn 2000; Accessed August 25, 2020).
Time to act
Open science looks ahead to a future where the capacity to share research findings is optimized through scholarly commons, collaboratives that steward research goods through the decades, and across the planet (See: Scholarly commons; Also, Madison et al. 2009). Patents subtract intellectual property and value from these commons: “[T]o the extent that universities surround the work of their scientists with thickets of patents, the upshot can be what Heller and Eisenberg [1998] call a scientific ‘anticommons’ in which ideas and concepts that in the public domain might spur discovery and innovation are zealously guarded by the institutional owners who value income more than innovation” (Ginsberg 2011). Researchers may also shy away from research arenas where existing patents impede new research (Foray and Lissoni 2010).
Looking ahead, the rapid increase of mostly under-performing (in terms of financial gain) patents creates no-research zones across formerly attractive knowledge domains. This growing patent infestation — intellectual property kudzu clogging the shared open resource pool — may be an unfortunate near-future end game for university patents, strangling new research. But a better plan is to clear away these anticommons today.
In the US, the repeal of Bayh-Dole — the act that permitted universities to patent federally-funded research — would open up old (and now, new), long-term research sharing capacities (Barnett, May 10, 2020; Accessed August 26, 2020). Putting the market-incentive genie back in its bottle will help universities shrink their administrative overhead, help researchers manage their own research interests, and help the academy get on with the real business of science: its mission to openly share knowledge within an abundant gift economy (See: Demand Sharing) in order to foster new discoveries of benefit to all humans.
However, Bayh-Dole is only one of a couple dozen post-WWII US laws that regulate and channel intellectual property flows among universities, government labs, and industry (Slaughter and Rhoades 2010). These laws were created to knit university research outputs into the surrounding neoliberal marketplace. Each of these laws needs to be reassessed for its impact on the other knowledge dissemination flows universities have long used, and on the long-term mission of academic organizations. As the U.S. Code is a maze of regulations that are stacked on previous laws, simply repealing one of these (such as Bayh-Dole) is rarely a good fix. Its removal simply exposes the problems created by the previous laws (Barnett, August 31, 2020; Accessed September 1, 2020).
There are two options around Bayh-Dole. The first would be a new national law that revokes and replaces large parts of Bayh-Dole without repealing it; a kind of Bayh-Dole antidote that neutralizes the previous law and adds another wart on the dimpled surface of the U.S. Code. The problem here, as John Wilbanks (personal communication) surmises: universities would likely find contractual means to work around the new law and keep doing what they do in a somewhat weaker mode. A university culture of neoliberal, short-term gain will find a way to circumvent the new law.
The second option is more pervasive and effective over time: change university culture to neutralize Bayh-Dole. “Any university could in effect repeal Bayh-Dole by creating an open scholarship favorable patent policy. Claim nothing up front. Require no disclosure of inventions” (Barnett, ibid). Here is a concrete cultural change that open scientists can take to their faculty senates and board of regents. Barnett (ibid) spells what needs to be done, and with some precision:
“Thus, the shortest route to open is to insist that universities comply with the extraneous requirement of the nonprofit standard patent rights clause at 37 CFR 401.14(f)(2) — require the written agreement, making inventors parties to each funding agreement, and declining to take any interest in any invention the inventors might make under the funding agreement (which in turn brings the university into compliance with the extraneous requirement at 37 CFR 401.14(g)(1)). With compliant (f)(2) agreements in place, inventors have no obligation to disclose subject inventions to the university or to the federal government so long as the inventors do not make the inventions know[n] to the inventors’ patent personnel and the university does not claim ownership of the inventions and require the inventors to make the inventions known to the university’s patent personnel.”
Once the university’s culture has pivoted to open, technology transfer offices (downsized appropriately) could play a part in encouraging open and free licensing agreements that seed new knowledge out to the public. “Universities have, for a very long time, seen themselves primarily as dedicated to the advancement of knowledge and human welfare through basic research, reasoned inquiry, and education. The long-standing social traditions of science have always stood apart from market incentives and orientations. The problem is therefore one of reawakening slightly dormant cultural norms and understandings, rather than creating new ones in the teeth of long-standing contrary traditions” (Benkler 2006).
Life after patents
There are some universities, and hundreds of active academics — and associate vice chancellors and assistant deans — who have benefited financially (or defended their job salaries) from university-patent-driven technology-transfer practices enabled by these laws. There is an argument that universities need this new source of funding in the face of other budget cuts; that universities should realize immediate returns of the value of their research. However, such an argument already discounts other, and greater, value that open research might provide in the absence of patents. The larger corrective to current budget issues begins with a more complete understanding of the sum of the value of the public goods created by universities.
Newfield (2016) details the path to more fully optimize the value proposition for universities:
“We saw that the road to the public university’s decline was paved with a long, diffuse campaign against its status as a public good. The practical effects were disastrous. The demotion of public good status forced university managers to pare their institutions’ overall value to a narrow and fragile private fraction of the total (the wage premium over high school graduation). This paring undermined the university’s ability to deliver the indirect, nonmarket, and social benefits that make up the majority of its total value, and its ability to deliver the emerging private market good, which were creative capabilities, which paradoxically could not be supported by private good market calculations. The failure to make a strong case for both individual and mass creativity, which depended on rebuilt support for research as well as instruction, weakened the case for rebuilt public funding. Collateral damage includes weaker understanding of the public value of academic freedom for faculty, of due-process-based job security for all university employees, and of the need to convert student work time to study time.
The solution requires restoring the university’s public good status. A first step would be basic accounting reform that quantifies the value of indirect effects, nonmarket value, and social benefits with the same dutiful attentiveness that accounting applies to the private market benefit of higher salaries” (Newfield 2016).
Open science looks to build on the longer-term historical/future mission of the academy as a wellspring for creative outcomes, both research and learning. All through this Handbook, you can find information and explanations on how open science cultural changes — many of which merely revitalize lost cultural norms — build innovation capacity and internal incentives that can drive science forward. Because of the compounding feature of open research collaborations, open science is likely to also improve the direct financial return on research within society, even though universities do not capture this return through patents.
Newfield (2016) proposes a multi-stage recovery from the neoliberal university. As open science works inside the academy to optimize the complete value of doing scholarship, this added value can become the subject of an active conversation with government funders and legislatures, who will be tasked to reinvest in the higher education endeavor as a public good with a solid value proposition.
Your take on this
You can help your university become more open by working toward a post-patent culture. What is your sense, from your own experience working with and around university-held patents? How much of your time is spent dealing with demands for patentable technology transfer? Has the presence of existing patents caused you to shift your research topic? The future of patents is one more conversation within the cultural shift toward open science. Your ideas are valuable, perhaps these should be gifted to the academy (See: Idea Gardening).
References:
Benkler, Yochai. The Wealth of Networks: How Social Production Transforms Markets and Freedom. New Haven [Conn.]: Yale University Press, 2006.
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.
Foray, Dominique. Economics of Knowledge. MIT press, 2004.
Foray, Dominique, and Francesco Lissoni. “University Research and Public–Private Interaction.” In Handbook of the Economics of Innovation, 1:275–314. Elsevier, 2010. https://doi.org/10.1016/S0169-7218(10)01006-3.
Ginsberg, Benjamin. The Fall of the Faculty. Oxford University Press, 2011.
Graeber, David. Bullshit Jobs: A Theory, 2019.
Heller, M. A., and Rebecca S. Eisenberg. “Can Patents Deter Innovation? The Anticommons in Biomedical Research.” Science 280, no. 5364 (May 1, 1998): 698–701. https://doi.org/10.1126/science.280.5364.698.
Hyde, Lewis. The Gift: Creativity and the Artist in the Modern World. Vintage, 2009.
Madison, Michael J, Brett M Frischmann, and Katherine J Strandburg. “The University as Constructed Cultural Commons.” Washington University Journal of Law and Policy 30 (2009): 365–403.
Mowery, David C, Richard R Nelson, Bhaven N Sampat, and Arvids A Ziedonis. “The Growth of Patenting and Licensing by US Universities: An Assessment of the Effects of the Bayh–Dole Act of 1980.” Research Policy 30, no. 1 (2001): 99–119.
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.
Newfield, Christopher. The Great Mistake: How We Wrecked Public Universities and How We Can Fix Them. JHU Press, 2016.
Slaughter, Sheila, and Gary Rhoades. Academic Capitalism and the New Economy: Markets, State, and Higher Education. Paperback ed. Baltimore: Johns Hopkins Univ. Press, 2010.
Stodden, Victoria. “Intellectual Property and Computational Science.” In Opening Science, edited by Sönke Bartling and Sascha Friesike, 225–35. Cham: Springer International Publishing, 2014. https://doi.org/10.1007/978-3-319-00026-8_15.
Strandburg, Katherine J. “Curiosity-Driven Research and University Technology Transfer.” University Entrepreneurship and Technology Transfer: Process, Design, and Intellectual Property, 2005, 93–123.
Welpe, Isabell M., Jutta Wollersheim, Stefanie Ringelhan, and Margit Osterloh, eds. Incentives and Performance. Cham: Springer International Publishing, 2015. https://doi.org/10.1007/978-3-319-09785-5.
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.
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.
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)
“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.
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.
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.
Time for dignity and fairness: and the value of caring. Artwork by Kelvy Bird: https://www.kelvybird.com/
“So it’s kind of like if your house catches on fire. The bad news is there is no fire brigade. The good news is random people apparate from nowhere, put out the fire and leave without expecting payment or praise. …I was trying to think of the right model to describe this form of random acts of kindness by geeky strangers. …You know, it’s just like the hail goes out and people are ready to help. And it turns out this model is everywhere, once you start looking for it.” Jonathan Zittrain, Ted Talk 2009 <https://www.ted.com/talks/jonathan_zittrain_the_web_is_a_random_act_of_kindness?>
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 welcome! Revised from a talk at the ESIP 2019 Summer Meeting. With travel support from the Alfred P. Sloan Foundation. Arigatou!
There are lots of ways that the rational, logical, hyper-competitive, winner-take-all, zero-sum, prisoner’s dilemma, nice-guys-finish-last, single-bottom-line, annual-productivity ratchet — or add your adjective here — mindset is just wrong for sustaining the academy and bad for science. For decades now, the same neo-liberal economic schemes that have been used to reshape how governments budget their funds have also made dramatic and disturbing inroads into university budgets and governance. Open science can show how that trend is a race to the bottom for universities. What do you say, we turn around and go another way?
“I have learnt silence from the talkative, tolerance from the intolerant and kindness from the unkind.” Khalil Ghibran, Sand and Foam.
A century without kindness: the impact of external logics
The banishment of kindness as a necessary part of being an academic, — just one more feature of adopting the neoliberal marketplace logic, and another effect of hyper-masculinity in the workplace — allows academics to defer judgements about kindness:
“We want to argue, however, that although kindness is a commonplace in pedagogical encounters, easily recognisable by its presence or absence, attending to it can be subversive of neo-liberal assumptions that place value on utility and cost above other human values” (Clegg and Rowland, 2010).
The word for kindness in Latin is humanitas: kindness makes us human. “[T]he Roman Emperor Marcus Aurelius, a leading Stoic philosopher, speaks of kindness as ‘mankind’s [sic] greatest delight’ (Phillips and Taylor 2009, 18). In Aristotle’s teachings, kindness is a component of phronesis: an entire type of “practical wisdom” that we’ve slowly devalued over the past 300 years (Juarrero, 1999) [ and you can blame Hume and Kant and all the usual suspects for this]. Phronesis combines virtue with a notion of adult comprehension: a way of knowing the right thing to do in all circumstances. It has little to do with intellection, and everything to do with broad experience and learning.
The road to a doctorate is long and difficult, and so adding another layer of learning to the process might seem short-sighted. And yet avoiding learning phronesis in your daily life is probably not any easier than practicing this, since the absence of phronesis leads to serial mistakes in moral and practical judgement, any one of which can be “career defining” in a negative sense. “Practical wisdom” is integral to “doing the right thing” while you learn to “do the thing right.” Doing the right thing often includes knowing how to exercise kindness with others.
A child can show kindness, and we welcome this. An adult (one who has learned some phronesis) can act kinder than a child, because this adult is experienced in a broader range of social circumstances and personal relationships. An adult can be — to use the Yiddish — a mensch. And a mensch can be kinder than a non-mensch or a proto-mensch. Lesson: be an open science mensch.
Kindness starts with intention
Real kindness begins with a clear intention. This adds an important aspect of self-judgement to its base. Without this aspect you cannot actually be kind, even if others might interpret what you are doing as being kind. How do you actually judge your intentions, particularly in relationships with other people and things? Something to contemplate. Also note: Clegg and Rowland (2010) remind us that kindness is not equated with leniency or “being nice.” Real kindness uses courage to articulate accurate observations and open learning moments that can be difficult and painful for both parties.
Kindness is something you learn and do
Kindness is a normative human practice in a wide range of social frames: parenting, friendship, governance, teaching, caregiving, civil interactions. Zittrain (above) reminds us that the internet was built on kindness and generosity. In nearly every human social endeavor, kindness matters. Even in highly-competitive sporting events, “sportsmanship” is highly valued, and is actually an internal normative form of kindness. Why should kindness, and critical interrogations about its role, be absent from research and management in the academy?
Like rationality, kindness is a form of practice, not an emotion. You can no more “feel” kind than you can “feel” rational. Unlike rationality, kindness necessarily involves others, their perspectives and needs. Kindness can and will also be judged by others for its qualities. Is it genuine? Is it motivated by a need to be perceived as kind? Is it effective in performing its intention? What is its intention? In the academy where intellectual judgements run wide and deep, kindness opens up another opportunity to be judged. But so does being unkind. Or it should. For decades, the lack of kindness in our research institutions and workplaces has gone unremarked. It is time to remark these.
Culture provides meaning to intentions
Again, kindness begins with intention. The same activity with different intentions can be a kind, caring conversation, or it can be a cruel interrogation. Intentions are themselves colored by culture. Culture provides a layer of shared meaning/learning that helps the individual (both the intend-er and the intend-ee) discover and interpret shared meaning as intended. You and the other person can answer the question: what did you mean?
The social world always contains this layer of culture. There is no society without it. Individuals hold this layer as a shared/learned resource. The cultural values (See: Values, freedoms and principles) you bring to your open science organization can assemble the meanings that add clear intentions to shared kindness. Just as some institutional cultures today — and inside the academy — support bullying and demeaning actions (NAS et al, 2018).
One feature of kindness is that it enables both halves of the double meaning of the term “care.” To really care about someone or something, you need to tap into genuine kindness. To care for someone or something can merely be a job. But this job is also reduced without the impulse of kindness. That is why it is time to…
Put care back in your career.
“[B]y infusing bureaucratic maintenance work with an ethic of care, we can challenge contemporary workplace attitudes surrounding “productivity” and “efficiency,” moving toward the recognition of maintenance itself as a valued contribution. We can also broaden access to systems of information, thereby supporting its generative value…” (Maintainers et al, 2019).
The Maintainers <http://themaintainers.org/> extend an ethic of care to each other and to their work: they keep everything running, instead of inventing new stuff. This ethic is born in kindness, and requires a level of humility not casually found in the academy, where intellectual heroics overshadow moral choices.
Nel Noddings, who is a “care theorist,” someone who makes “the caring relation basic in moral theory” (2003), looks to recenter care as a normative behavior in education and the academy. She also separates the care that is expected in work (for example, doing something really well, or managing the needs of a student/patient) as a conformity to a workplace ethic, from caring: human acts “done out of love and natural inclination” (Noddings, 1988). What really works — in teaching and learning, and in team dynamics for collaborative research — is not completing the task of due-diligence, but rather building a framework of mutual caring nurtured from authentic kindness.
Bringing care into this discussion has now moved us away from communities, cohorts, and institutions. Care directs us back to intentions that are articulated in culture, but which also speak to being human in a mutually responsible human environment: a phrase not usually descriptive of the academy. “[W]e are led to redefine responsibility as response-ability, the ability to respond positively to others and not just to fulfill assigned duties” (ibid).
Open science is also science done through care and kindness: science that much more resembles the model of peer production within a commons, than it does a winner-take-all corporate struggle. “[W]ithout receiving conventional, tangible payments or favors in return, peers exercise kindness, benevolence, charity and generosity” (Benkler and Nissenbaum, 2006). Open science demands new levels of response-abilities: based on new and expanded academic freedoms (See: Values, freedoms and principles) and internet-enabled collaborations.
Coda: There are a lot more articles and books (such as Phillips and Taylor (2009): On Kindness) about the history of kindness and care that point out how these virtues were heralded as the basis of human happiness for centuries, and only recently (last 3–400 years) have these been eclipsed by more individualistic moral models (thanks to Hobbes, Kant, etc. — the usual suspects). So… practicing open science may also be good for your happiness. Doing open science can improve your happiness, and the happiness of those around you. How about that?
References
Benkler, Yochai, and Helen Nissenbaum. “Commons-Based Peer Production and Virtue.” Journal of Political Philosophy 14, no. 4 (2006): 394–419.
Clegg, S., and S. Rowland. “Kindness in pedagogical practice and academic life.” British Journal of Sociology of Education 31, no. 6 (2010): 719–735.
Juarrero, Alicia. Dynamics in Action. Cambridge, Ma: MIT Press, 1999.
National Academies of Sciences, Engineering, and Medicine, NAS Committee on the Impacts of Sexual Harassment in Academia, Committee on Women in Science, Engineering, and Medicine, and Policy and Global Affairs. Sexual Harassment of Women: Climate, Culture, and Consequences in Academic Sciences, Engineering, and Medicine. Edited by Paula A. Johnson, Sheila E. Widnall, and Frazier F. Benya. Washington, D.C.: National Academies Press, 2018. https://doi.org/10.17226/24994.
Noddings, Nel. “An Ethic of Caring and Its Implications for Instructional Arrangements.” American Journal of Education 96, no. 2 (1988): 215–230.
— — — . Happiness and Education. Cambridge University Press, 2003.
Phillips, Adam, and Barbara Taylor. On Kindness. 1st American ed. New York: Farrar, Straus and Giroux, 2009.
In a famous letter of 1813, Thomas Jefferson compared the spread of ideas to the way people light one candle from another:
“He who receives an idea from me, receives instruction himself without lessening mine; as he who lites his taper at mine, receives light without darkening me.”
Share what’s important to you. Demand what you need. Photo Credit: Hartwig HDK on Flickr, CC By-ND 2.0
Demand sharing means you can ask for everything you need to do your science… with one proviso…
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’ve all heard about the “sharing economy,” where we can gain new streams of income or convenience by simply sharing excess capacity (that spare room, the car ride, an electric scooter, etc.). And we’ve been told since childhood that sharing things we no longer need can help those with greater needs. Most of us feel we have a good idea about what it means to “share.” But then most of us are also mistaken, and here’s why.
Anthropologists who look at the ethnographies (and who do their own) of hunter-gatherer groups, and who sometimes also look at modern attempts to create sharing economies (e.g., Uber, Airbnb, etc.), tell us several things about sharing that most of us may find new and different from what we expected (Widlok, 2016; Suzman, 2018 <https://aeon.co/essays/why-inequality-bothers-people-more-than-poverty> Retrieved May 6, 2019). These ideas about sharing, synthesized from the study of human groups that have been successfully building their own lives for tens of thousands of years, say to us that we have “sharing” almost completely wrong.
For example:
• Real sharing is not charity. Charity is an artifact of the marketplace (and of personal wealth) and the logics of artificial scarcity.
• Sharing something you own that you are not using (like a spare room or space in your car) in exchange for cash is just another form of market transaction.
• Giving away things that you don’t need or no longer want is not a good example of sharing. This is an edge case.
Demand Sharing: share what is most important to you. Get what you need in return
In this handbook, we use the phrase “demand sharing” to designate a culturally advanced form of sharing, a type of cultural behavior that has been in widespread use of the majority of the human population for tens of thousands of years, and only recently eclipsed by marketplace logics in the past two to three hundred years. “Millions of years of evolution have designed us to live and think as community members. Within a mere two centuries we have become alienated individuals. Nothing testifies better to the awesome power of culture” (Harari, 2014).
Society uses demand sharing to fund its needs
A rather good (perhaps unexpected) example of demand sharing in modern society is having your representative government demand a tax that everybody pays, which then, for example, supports your state’s public colleges and universities (and pays your salary). That’s right; taxation is how a society demands of itself those resources it needs to prosper (Widlok, 2016).
Another example is sharing within a household, where family members can grab a snack from the refrigerator without much bother or need to justify or account for their choices. In the case of the academy, the “refrigerator” is the rapidly expanding corpus of digital research objects, and the family is fellow scientists who stock this with the outputs of their work, and who can then dive in and grab what they need for their own research. Note: this is a never-empty refrigerator, as these digital objects are not used up by their taking. Note again: they are anti-rivalrous: they gain value when they are shared. This is something every open scientist needs to remember.
Teaching and learning already require demand sharing. As an open scientist you’ve probably taught in a variety of classroom situations. Your students asked questions to extend their learning. Your best students (bless them) outright demanded to be taught. They marched into libraries (buildings, or on-line) and demanded the resources they need. They came to your office hours and demanded answers to their quandaries.
This means that nearly every scientist is well versed on how to participate in a demand-sharing economy. First, the state demands that its citizens fund the university, supporting teachers and learning. Then the student shows up and demands to be taught. We all did this as students. It’s not obscure, it’s how we learn.
Imagine a professor giving a lecture who stops in the middle and says, “This next part is really interesting; if you want to learn it, go to my app on your phone and deposit $10.” This should sound bizarre to you (if it doesn’t, then the neo-liberal university is your real home).
The for-profit textbook industry is very close to this same idea, particularly when a professor assigns their own textbook.
In part it sounds strange because the professor’s salary is already paid, hopefully through taxes. But mainly, it sounds wrong, as professors (who were once students) are completely happy for their students to learn. These learning moments in the classroom are seen as socially important and personally rewarding. When a student asks you a question, you do your best to help them learn something new.
In the hunter-gatherer culture, when a child comes to your fire and asks for some bit of meat from your catch, you always give it to them. Like food at a hunter-gatherer fire, information in a college is something that can be demanded. Demand sharing in education is a type of cultural economy where the norms and rules — the times and places, the manner of asking, the desire to teach and the value of learning — are well-known, without being written down. Students know they cannot demand the answers to a quiz in advance. What is sometimes forgotten is the need for and role of kindness in these interactions; more about that a bit later in the handbook (Deep Dive: Kindness).
Got a PhD? You know how to demand what you need
This means that you already know how to do demand sharing. Let’s look how demand sharing differs with what we just described as poor examples of “sharing.”
• You don’t give your classes as a form of charity (even though you may consider your own salary inadequate). You are a professional. Teaching is important. Your students have legitimate demands on your knowledge and your kindness. Passing on knowledge is why you teach.
• You also don’t teach your students content that you find worthless to you or loan them books that you are no longer satisfied with, unless these books are instructive in other ways. You share what is really important to your professional life: the best knowledge you’ve acquired.
• You expect students (at least, grad students) to demand from you what they need to learn and grow as scientists.
Demand sharing means sharing what is important to your research
This is the proviso we mentioned above. The same demand-sharing logic that collects the taxes that pay your salary, and enables your students to learn, also enables the academy to manage its knowledge resources for the benefit of all scientists, and the planet through the internet. Until today, a scientist might legitimately point out the huge amount of process-friction that would overly complicate sharing her data or workflows. A lot of the work of open-science advocates in the last two decades has been focused on reducing that friction through web-based platforms and services. Much of the remaining friction is cultural; linked back to institutional practices that do not reward or actively punish open resource sharing.
In an open-science, demand-sharing academic culture, sharing as much of your research as early as possible is a virtue strong enough to be a norm. Share what matters most to you: your methods, your findings (even null fundings), and your data. Share your best ideas openly, not simply those ideas that you have no interest in pursuing and every interest in having someone else pursue (See also: Idea Farming). Share your knowing by listening and adding to the conversation.
Open science requires generosity with a simple promise: each scientist will get more than they give. That’s the bargain the academy makes with you when you join and actively participate in the open-science academic society.
Of course the whole push to reboot the academy is based on the premise that this bargain has been bent and broken in many places.
This bargain is bolstered by the network effects of academy organizations. Demand sharing optimizes this bargain across academic networks and clubs (Redaction, 2016; Retrieved June 1, 2019).
Sharing imbeds your work into the community of science as a gift, a form of offering that also signals your membership. Sharing includes reviewing and acknowledging the work of your peers (See also: Perils of peer review). The open-science community creates its internal authority through relentless self-critique.
This authority works through a special soft of reciprocity and a level field of mutual status. As Polanyi (1962) noted, “[O]nce the novice has reached the grade of an independent scientist, there is no longer any superior above him. His submission to scientific opinion is entailed now in his joining a chain of mutual appreciations, within which he is called upon to bear his equal share of responsibility for the authority to which he submits.” This reciprocal authority of “mutual appreciations”, based on openly shared and critiqued knowledge is the basis for all applications of authority and leadership in an open-science academy (See also: Leadership and sharing).
The offerings you provide to the “republic of science” (Polanyi, ibid) lend you the cultural capital to demand the resources you need for your work from the abundance of open-access resources, and the knowing of others in your field. These, in turn, offer up their research for your use. As Hyde (2009) notes, the “constant and long-term exchanges between many people may have no ultimate ‘economic’ benefit, but through them society emerges where there was none before”; your contributions help create the academy society.
Amplified by the internet’s global reach, these exchanges expand and accelerate the process of science. You share the most important ideas you have, even at the risk of being scooped, because getting the most important work done now — whether you do this or someone else does (and attributes you with the idea) — moves science forward. You share your research results, all of them, knowing you will be critiqued by your peers, as you will also critique theirs.
“The self-image of humans who are embedded in sharing relations is not one of homo faber who creates his or her world out of nothing and without anyone else. Rather it is an image of what I have called homo sumens … who takes into use what is available through the company of others and that can be claimed from them” (Widlok, 2016).
Academic clubs: collectives for research collaboration
Demand sharing is a dense cultural practice, with its own behavioral expectations. When you share, you signal your desire to be included in the community. What you must learn, then, are the guidelines for demanding resources. “[T]he problem is not one of deciding what to give to whom but rather what to demand of whom. The onus is on the potential receiver to make his or her claim acceptable and the rules for appropriateness are not about acceptable giving but acceptable demanding” (Widlok, ibid; emphasis added).
The cultural shift to demand sharing will create a social basis for new science collectives, for “clubs” that share internally as though the club were a single, social organism. These formations are not entirely new. R&D Think-tanks have been funded for this purpose, and the NSF in the US spends a billion dollars a year funding academic workshops to assemble temporary collectives to solve common problems. “Club goods” are non-rivalrous inside the club, but not necessarily without shared costs (Hartley, et al, 2019). Thomas and Brown (2011) describe these as well, “Collectives are made up of people who generally share values and beliefs about the world and their place in it, who value participation over belonging, and who engage in a set of shared practices. Thus collectives are plural and multiple. They also both form and disappear regularly around different ideas, events, or moments.” Collectives enable collaboration across the internet, inform team-building, and open up the cultural situations for shared knowing.
The cultural practices of demand sharing will be emergent in the academy as open resources — including access to and discoverability of collaborators — become increasingly available in the next decade. This Handbook will help you to kickstart your own collectives, and forge demand-sharing cultural norms that suit your situation; see also Building new collectives.
Together with “fierce equality,” demand sharing as a cultural norm can help realize an actual sharing economy for the academy, separated from the arbitrary scarcity of the neo-liberal marketplace; a gift economy grounded in mutual appreciation and reciprocity. The particular practices of demand sharing will need to grow inside thousands of institutions across the globe. A goal of this Handbook is to give you the resources you need to build demand-sharing logics inside your academy homes. You can be a demand-sharing culture change agent by sharing your research objects and your research questions and problems; by listening more and adding your knowledge when asked. Demand answers from others; learn together. It’s science, not alchemy. You are not alone.
References
Harari, Y.N. Sapiens: A Brief History of Humankind. Random House, 2014.
Hartley, John, Jason Potts, Lucy Montgomery, Ellie Rennie, and Cameron Neylon. “Do We Need to Move from Communication Technology to User Community? A New Economic Model of the Journal as a Club.” Learned Publishing 32, no. 1 (January 2019): 27–35. https://doi.org/10.1002/leap.1228.
Hyde, Lewis. The Gift: Creativity and the Artist in the Modern World. Vintage, 2009.
Polanyi, M. “The Republic of Science: Its Political and Economic Theory.” Minerva 1 (1962): 54–73.
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.
Widlok, T. Anthropology and the Economy of Sharing. Routledge, 2016.
“Religion is a culture of faith; science is a culture of doubt” Richard Feynman (unsourced).
“Don’t think of culture as other than accumulated learning that sits inside you as one of your layers of consciousness” (Edwin Schein, 2016 <https://www.youtube.com/watch?v=6wJaNKIALLw> accessed April 4, 2019).
“‘Culture’ is everything we don’t have to do” (Brian Eno, 1996; W Magazine)
“‘Culture’ is anything you can get better at” Bruce Caron, 2019.
All the culture that fits: exploring the work of culture to prepare to change it
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 want culture in the academy to work for us, instead of against us. The many meanings of the word “culture” — each with certain claims to capture essential aspects of this spectrum of human proclivity and activity — make the task of outlining a notion of the “work of culture” also a chore of definitions. What is it about culture that can be said to do work? And what work is important for open science?
One goal of this book is to help scholars who have little or no background in the academic study of culture to gain a sufficient purchase on this notion to become confident, productive agents of culture change for their home institutions, their professional associations and research organizations, and for the academy as a global science endeavor. Like quantum mechanics and machine intelligence, the serious study of culture is not one of these “dip your toes in the shallow end” kind of endeavor. However, with a roadmap through just enough of this contested space, even tenured chemistry professors (or pick your discipline) can become bonafide organizational culture-change agents.
Getting back to basics
Beginning anthropology classes might spend a month covering the “history of the anthropological ideas of culture.” These notions developed first through colonial excursions, and then with missionaries and colonial settlers, and finally ethnographers. Courses on “organizational culture” are now required in MBA curricula and iSchools.
Arjo Klamer (2017), a Dutch economist, introduces culture to his economics class by adding two meaning domains for this word: culture as the accomplishments of a society (e.g., baroque style as a form of European culture), and culture as creative activity within sectors of the economy (the arts, architecture, music, etc.). His first meaning gives us the adjective “cultured,” applied to individuals who exemplify a certain noticeable style; while his second is where you go to when you click on the “culture” link in an online magazine or newspaper.
“Culture” is a section in your newspaper/magazine/webzine
Culture as a process
Folks who want to use culture and culture change as a resource or a tool to change social groups describe culture as a process. They then offer a method to intercept and guide this process (Marcus and Conner, 2014). Organizational management researchers are full of advice on the culture of organizations, but usually fail to look at how this type of culture fits into the larger sense of culture’s role in society or in individual identity. Anthropologists describe cultures and how these change without intervention, but little advice on how to intentionally change this. Here, you will find both anthropological and organizational perspectives, just so you are fully comfortable that you’ve travelled the entire landscape of the term “culture.”
Do you own your culture, or does your culture own you?
“Culture is public because meaning is” (Geertz, 1973).
Much of the disputed territory for culture, whether as an object of study, or as a field for intentional change, is centered on how culture is carried more or less unconsciously by the individual. Sometimes it feels as though we’ve been “marinated” in cultural practices our entire lives: language, cuisine, music, art, and now online content. There is a part of culture that is tacit, embodied, unspoken, and non-conscious. Culture theories tell us this, and they are not wrong. This aspect of culture is often used to demonstrate how difficult it is to manage culture.
A vague, squishy word, indeed
Jean-Louis Gassée (not an anthropologist; but rather of Apple, BeOS, and Palm fame), in a blog about Intel’s “toxic culture” writes:
“Our powerful human emotions are bundled into something we call Culture, itself a vague, squishy word……Culture develops within us in a manner similar to our taste buds: Our gustatory education starts with Mother’s milk and accumulates over time. The trouble with our acquired tastes, particularly in the realm of ideas, is that they drop below our consciousness: Raw data are filtered, judged, and labeled before being passed to our conscious, ‘rational’ processes.”
Gassée is pointing out that parts of the repertoire of shared meanings, behaviors, and sentiments that people would label “cultural” are known without any explicit knowledge of how and when we came to know these; and even less ability to describe them.
Schein (2010) calls this a cultural “layer.” This layer is learned from birth at home, and then in school, and then in the workplace, where the same tacit layer proves the hardest part to change. When your company/university/agency is running on a tacit culture layer, instead of on a reflexive intentional culture layer, it is most vulnerable to becoming toxic (Deep Dive: Toxic Culture).
Science is a reflexive, interrogative activity
Fortunately, the main aspects of academy culture we are hoping to change can all be made explicit and available to reflexive rebooting. In fact, open science is not reinventing science as much as clearing away the extraneous cultural underbrush (such as journal impact factors) that has collected in the past half-century or so. Scientists can openly interrogate these practices, and collectively move away from perverse incentives, conflicts of interest, and culturally-supported bad behavior in the academy. The leading advice to Silican Valley CEOs today is to avoid “f*cking up your culture” (See also: Don’t F*ck Up Your Culture; Retrieved May 17, 2019). The academy might want to listen here.
You cannot really avoid culture if you want change
A good point is worth saying twice: you may be an open-science pioneer who is eager and intent to bring productive changes to the academy, and yet still be uncomfortable with the notion of culture. You might prefer to offer solutions (e.g., coercive rules enforced by governments and funding organizations, novel technology platforms, and manifestos — so many manifestos) that, you hope, would shape “social behavior” without needing to confront or even consider culture. You look at the term “culture” and see a morass of competing meanings, with tangled and complex implications for the use of the term. How do you defend a program to change culture when you can’t get any three people in a room to agree on what culture means?
Scientists are many things. Each of these things have something in common: a desire for precision. The “vague, squishy” term “culture” offers very little precision and a whole load of ambiguity and complexity. As a scientist, you already have your hands full of ambiguity and complexity; you are striving to understand the inherent, emergent complexity of the universe. You rely on instruments that achieve ever-better accuracy and precision to help you extract some level of near-certainty to observe your object of study.
Many scientists are dismayed by the sheer amount of fuzziness surrounding the notion of culture. So the project at hand is to un-fuzzy that corner of culture where the academy can work on intentional changes to promote open science. The rest can remain terra incognito. The fact is, you don’t need to be an anthropologist to put culture to work in your organization.
In short: the good news is that the cultural work of open science is centered on those aspects of culture that can be intentionally described, discussed, and refactored — even if some of these might later become routine and get framed as default expectations. It’s not a bad thing to have your active culture also inform the tacit level of culture, it’s actually a goal: norms are cultural behaviors and attitudes that have become tacit culture. A norm is when “we open scientists do things like this,” and think: why would we do anything else?
Culture: trimmed down to size for the open scientist
Here we will trim the semantic tangle of the term “culture” to a more specific notion of culture: to the point where it can serve our understanding of how this works and how this fits into the future of the academy. The word “culture” will still hold all of its diverse and multiplex meanings everywhere else, however, here we’ll just agree to use it in one specific way to cut through a lot of the semantic shrubbery it has acquired over the centuries and around the globe.
Learning from anthropology
We can start by looking at some general attributes of “culture.” In his 1993 book, Culture, Chris Jenks notes (following Ralph Parsons):
“…for present purposes three prominent keynotes of the discussion [around culture] may be picked out: first, that culture is transmitted, it constitutes a heritage or a social tradition; secondly, that it is learned, it is not a manifestation, in particular content, of man’s genetic constitution; and third, that it is shared. Culture, that is, is on the one hand the product of, on the other hand a determinant of, systems of human social interaction” (Jenks 1993: 59).
Lets put these verbs into the following order: learn (first exposure) → share (locally) → transmit (across space/time). Repeat as needed. This sounds a lot like education, something the academy already does. For the individual, this process is, or can be, a lifelong activity. What Clifford Geertz reminds us is that these cultural activities are public. Nothing is cultural until it is shared. That means these activities are available to study, and to change, and to be changed through intentional intervention (although somewhat less available when they are only tacit).
One easy way to see what Jenks is proposing here is to substitute “language” for “culture;” after all, language is a good part of any society’s cultural repertoire. Saying that language is transmitted is to acknowledge that we don’t need to invent our own language anew every generation. Saying language is learned explains that we acquire this through learning as children and then hone this learning throughout our lives. To say that language is shared points to a key concept: we need others to make this work; it’s called “conversation”. In many ways, language is primarily a type of sharing. Other skills and cultural content exhibit these same features.
The reverse is also true. If a language is not transmitted over time it “dies”. If a person doesn’t learn a language, they are left outside the conversations that happen in that language. And when a language ceases to be shared in everyday life (e.g., it becomes a “sacred” language that can only be spoken in certain places/times), other language forms will take over in daily life. Languages change all the time. Remember that. They manifest lifelong, tacit cultural practices, and they still change.
Culture comes in community boxes
“Community, therefore, is where one learns and continues to practice how to ‘be social’. At the risk of substituting one indefinable category for another, we could say it is where one acquires ‘culture’” (Cohen, 1985).
The usual container for a culture is called “community.” As an organization grows and governs its own cultural work, you can say that the group becomes a community. You can dive into “community” elsewhere in the Handbook (Deep Dive: Communities, Collectives, and Commons). Notions of community will also be threaded into many of the Handbook chapters.
Meaning, Symbols, and Memes; oh my!
Exactly what is learned, transmitted, and shared as culture is complicated. “Meaning” usually pops up here, together with “symbols” (meaning carriers). In many ways anything that can be learned (anything you can get better at by learning this), and that must be shared in order to make sense as something to do (write a song, choose a new fashion statement, enter a conversation, sports, theatre, etc.) becomes culture when the various meanings of that learned behavior are also shared. You cannot have your own private culture. That said, you can have a very small community with its own distinguished cultural behaviors.
Memes are symbols that have been reimagined as cultural-genetic replicators. The analogy to biology is intentional, and meme theorists also talk of culture change as evolution. Since the 1970s, meme theories have been proposed to explain how certain cultural content packages spread and persist.
“[Richard] Dawkin’s way of speaking was not meant to suggest that memes are conscious actors, only that they are entities with interests that can be furthered by natural selection. Their interests are not our interests. ‘A meme,’ [Daniel] Dennett says, ‘is an information packet with attitude’” (Gleick, 2011).
The notion of a meme is centered on the idea that humans as social beings are shaped by culture the same way their bodies are shaped by their DNA. If you want to explore memes a bit more, here’s a good introduction (by Dennett) and some good counter arguments (by Lanier). Here we will talk about meaning and symbols and culture change, but you are certainly free to talk about memes and evolution. You can also look into “cultural science,” where evolutionary cultural studies are being done.
Culture is a plural noun
Not grammatically, of course, but we have seen and continue to see around us how cultural notions, skills, and activities are typically multiple, contested, fragile, and liable to change. Individuals tend to privilege those notions, skills, and activities they have invested time to learn (so nobody wants to be forced to use a different language). However, since culture must be shared to be viable, individuals continually find themselves in conversation with others who have differing cultural inventories. Culture is like a life-long song we only sing once, and none of us has been handed the score for the next chorus. We just keep on singing, in multipart harmony.
Knowing is the intrinsic work of culture in your organization
Of course, culture is not only a noun. Humans are cultural beings. Humans have culture. Humans do culture. There is a lot of culture going on all the time. More recent takes on organizational culture reject this as being just some packet of ideas that gets passed around.Today, more than ever before, culture is viral, active, flowing (Appadurai, 1996). Today, culture is on the internet too.
The recent work of John Seely Brown, 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 (Cook and Brown, 1999). Instead of organizations stewarding an inventory of knowledge objects, what they need to do is open up contexts and spaces for knowing: contexts for the transmitting, learning, and sharing between and among their participants (Thomas and Brown, 2011).
This concept was then picked up by David Snowden and others (Kurtz and Snowden, 2003), who mapped the contexts of knowing and “sense-making” into what they called the Cynefin Framework (https://en.wikipedia.org/wiki/Cynefin_framework, Retrieved May 20, 2019). This framework is largely about identifying types of knowing — and ways of deciding — in corporations, as a corrective to the prior knowledge management systems which only covered tacit and discursive knowledge objects (Wenger et al, 2002).
“The framework sorts the issues facing leaders into five contexts defined by the nature of the relationship between cause and effect. Four of these — simple, complicated, complex, and chaotic — require leaders to diagnose situations and to act in contextually appropriate ways. The fifth — disorder — applies when it is unclear which of the other four contexts is predominant” (Snowden and Boone, 2007).
The Cynefin Framework describes several domains of knowing; the core qualities of knowing are different in each of these. Knowing is an activity, an action, not a commodity, not a thing to be managed.
Knowing, or sense-making, is an intrinsic work for organizational culture. This is particularly true in the academy, where new knowledge and learning outcomes are a chief value proposition. Scientific “knowledge” is an output of shared knowing.
The challenge is that these domains are not always fully manageable, and neither are the humans that engage in knowing with each other, most particularly in the complex domain of the infinite game. Knowing is why we might learn more in a 10 minute conversation than we can from a 1000 page book. Knowing is how scientists play the infinite game with one another. You can briefly explore the infinite game by going back to the Things about science section.
Cynefin for the Academy
For now, the main take-aways from using the Cynefin Framework for the academy are the following:
First: it helps to explain the difference between doing science, talking/writing science, and telling others about science. These occur in different domains; and,
Second: it begins to describe the complex, emergent space of the infinite game. Learning this is central to building academy governance for game play. For centuries, most scientists, or earlier, natural philosophers, and before them, philosophers, played the infinite game individually. Today, science and learning is a team sport, and the academy needs to find ways to govern team play (Deep Dive: Knowing to Play the Infinite Game).
The domains of decision-making for open-science organizations. Which domain does your organization currently use to make its decisions?
The Cynefin Framework is explored at length in Deep Dive sections on Leadership and Learning, so we will not pursue it further here, except for this: The Handbook also presents a version of the Cynefin Framework that uses three modal types of cultural activity to represent the framework’s logics (complex, complicated, simple). These modes are: festival, game, and spectacle. You will need to ask this question a lot: upon which logic does your organization base its decisions? Starting with the wrong logic will lead to bad, sometimes very bad, decisions. A lot of toxic culture in the academy is based on decisions arrived at in the wrong domain.
Festival: For those who grew up in the parts of the planet (such as most of North America) without festivals that involve actual danger, nudity, running with fire, social exposure, complex body skills, radical comedy — the various ingredients of festivity that make these events complex, emergent activities — we are not talking about the annual petunia festival here. Also note that the best intellectual conversations are like running with fire.
The Cultural Work of Social Organizations
Cultural practices and social organizations are intertwined in time and space. Social organizations are the social “appliances,” the furniture, that anchor human groups into more durable cultural contexts, which they support and are, in turn, supported by. These contexts expand our capacity for collective action, including economic and political action. Just as we do not need to—or get to—invent our own language, we don’t get to invent most of the social groups we intersect in our lives. But we can change them.
In order to pursue the intrinsic cultural work of the academy, we build communities inside organizations that use governance processes to support sharing knowing. We use can our organizations to manage other, social and economic tasks. If knowing is a dance, then community is the dance floor, and the organization is the dance hall.
In the twenty-five years since Jenks’ book, culture has seen a lot of new attention. From the portmanteau academic discipline of “cultural studies” to the cubicles of Silicon Valley start-up companies, the importance of culture for the everyday life and future prospects of societies and corporations has become a central theme. It’s high time for the academy to take a culture turn. You can help.
Now you know enough about the various aspects of culture to start rolling up your pants and wading in. You know that culture is (and must be) learned, shared, and transmitted. Most of culture is really vulnerable to intervention or substitution. Culture describes a broad range of human activities and a layer of meaning that is spread over (or under) social activities and organizations.
Knowing is an intrinsic work of culture, a primary activity for all cultural activities, but particularly for those, like science, that are involved in the infinite game. Knowing happens in more than one domain. The meanings of culture are all public. You can find them, interrogate them, and, yes, change them. That’s the next topic in the Handbook: The task: culture change.
References
Appadurai, Arjun. Modernity Al Large: Cultural Dimensions of Globalization. Vol. 1. U of Minnesota Press, 1996.
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.
Cohen, A.P. The Symbolic Construction of Community. Chichester, Sussex: Ellis Horwood Ltd, 1985.
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.
Geertz, C. The Interpretation of Cultures. New York: Basic Books, 1973.
Gleick, James. The Information: A History, a Theory, a Flood. 1st ed. New York: Pantheon Books, 2011.
Jenks, Chris. Culture. London And. New York: Routledge, 1993.
Klamer, A. Doing the Right Thing: A Value Based Economy. 2nd ed. London: Ubiquity Press, 2017. https://doi.org/10.5334/bbb.
Kurtz, Cynthia F, and David J Snowden. “The New Dynamics of Strategy: Sense-Making in a Complex and Complicated World.” IBM Systems Journal 42, no. 3 (2003): 462–483.
Markus, Hazel Rose, and Alana Conner. Clash!: How to Thrive in a Multicultural World. Penguin, 2014.
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.
Wenger, E., R.A. McDermott, and W. Snyder. Cultivating Communities of Practice: A Guide to Managing Knowledge. Harvard Business Press, 2002.
This is the introductory talk I presented at the 2018 SciDataCon in Botswana.
Let me begin by saying how gratified I am to be here, and to see all of you, many of whom are unmercifully jet lagged, as I know I am.
I want to thank Mark Parsons for doing all the heavy lifting to organize this session, and I thank all the speakers for their hard work. We lost a few speakers when their institutions wouldn’t support international travel… This demonstrates a situation that local academics face every time they try to travel to conferences in the North. Anyhow, with fewer talks, we will have more time for discussion.
My talk is about commoning around data resources on a global scale. Commoning, I argue is the destination that open data and science deserves.
For more than a decade, open science advocates have been building the infrastructure and the cultural sentiment to support open sharing for science objects, from ideas, to work flows, to data, publications, and peer reviews, and to whatever comes next.
One vision of what should logically come next is a move to internally-governed academy commons. I use this term in the plural here, anticipating a great variety of these, where institutions, careers, and scientific research can be fostered outside of the global marketplace.
The exvestment of academy content, careers, and communication from the global capital marketplace will require numerous experiments in alternative markets and governance schemes.
In many ways, however, it also means a return to how science operated not so very long ago, only with new opportunities provided by the internet and subsequent technologies. We are looking at science as a public good — scientists produce real public goods too, in terms of new knowledge and a better informed citizenry.
We expect taxes will pay for this, and we can support the value of science to our governments in many different ways outside of capital-market based returns. That is why we now turn to building science commons.
Most of these commons will be localized experiments — localized, that is, through specific disciplines and their internal data resource needs, through the mosaic of academy institutions and repositories and their capacities for data storage and use, through agencies and funders with their need to advance specific science outcomes, and through a range of funded research endeavors where scientists collaborate between institutions and across national boundaries.
Ideally, these commons will be localized to foster cultural innovation based NOT on importing these ideas from the global north, but rather, beginning with local voices and local cultural issues in every corner of the planet. Science is science from Gaborone to Geneva. Out of this panoply of knowledges, capabilities, and visions, academy commons can be built and internally governed across the planet. This is the task ahead for open science.
We have to be clear that we are also talking about “data-near governance” for these commons: about ownership and stewardship by and for the individuals who really need these data, about collaboratives of scientists whose particular research depends on the long-term stewardship of specific shared data resources.
Collective ownership of the stewardship practices for these data will form the infraCULTURE and governance focus for international data commons in the academy. These governance schemes will need to be negotiated with the various repositories where the data are held.
In order for these commons to reinforce each other and so to build a planetary solution, they must also follow shared design patterns and interoperable cultural norms resulting in shared standards and principles.
These patterns and norms also inform the logic of commoning.
Look around today and you can see hundreds of newly fashioned open-science programs and software platforms being fashioned by a vanguard of scientists.
These are the launchpads for our shared cultural journey into the future of open science.
Here we are in Botswana. What a wondrous country this is. I was here some decades ago and I had the opportunity to visit some of its great natural preserves. If you buy me a gin and tonic some evening, I will tell you about the time I was stalked by a lion near Shakawe up on the Okavango…
Botswana also holds a special place in current theories of commoning and sharing economies. It turns out that AfroFuturism can be found not only in a fictional nation of Wakanda, but also in the deep, first-growth, hunter-gatherer cultures of Botswana and Namibia.
An advanced form of commoning can be found in the cultural logics of the sharing practices of traditional San societies in Botswana. Recent ethnographies by James Suzman and Thomas Widlok, for example, outline two powerful cultural norms found in traditional sharing economies that are significantly absent from today’s cosmopolitan, market-based sharing economies and services, such as Uber and Airbnb.
The ethnographies describe these norms as “fierce equality” and “demand sharing.” These norms, they claim, could productively inform modern sharing economies anywhere in the world; economies that can outcompete against Uber in the long-term.
Here I claim that these norms can help propel academic commons away from the perverse market incentives that currently intercept and corrupt the scholarly process. What Yochai Benkler calls “the tyranny of the margin,” the ratcheting up of ever larger productivity demands by the marketplace: this is the lion that stalks the whole academy. This is why we need to build commons and safeguard our practices with really strong shared norms.
What might these norms look like inside the academy?
Fierce equality puts the norm of equality first, at all levels of science. And yes, this is where #MeToo and #TimesUp enter into the heart of the cultures of science. But there is more:
Fierce equality will prompt significant changes to how societies, universities, and funders view and support the science endeavor. Fierce equality militates against what Cameron Neylon calls bullshit excellence and privilege in the academy, against the gamification of careers and reputations using external metrics, such as journal impact factors, and ultimately against all forms of the “Matthew effect” that amplifies inequality in funding and recognition.
“Demand sharing” takes “open” to its logical destination: every scientist on the planet has a need to find the resources that support her research. Any scientist should be able to demand their share. This demand is not automatic, however. It’s not some academy birthright. It doesn’t come with your PHD.
The cultural workings that support demand sharing also require that each scientist be open to sharing what is most valuable to her: data, of course, and findings, but also questions and concerns, pain points and critical observations, help for others as needed, and perhaps even kindness.
It’s interesting how difficult it is to consider kindness as a core norm for science. Why is that? I’ll leave this one hanging here… It’s another talk.
Injecting the norms of demand sharing and fierce equality into the cultures of the academy will require the widespread adoption of emergent intentional and reflexive cultural practices. Refactoring infraculture takes a lot of time and work.
Why should we bother? What do we get in return?
Here is one thing:
Science has already started the technological move from a logic of arbitrary scarcity and scarce data resources to a logic of resource abundance. This move is central to Fourth Paradigm science and the future of big-data use. The challenges of and the opportunities for a science based on data abundance is what brings us all here this week.
At the same time we build the cyberinfrastructure, we also need to build the cyberinfraCULTURE to grow the practices that support active sharing, mixing, mining and reuse of data and other science objects. Science will never achieve the full potential for resource abundance by clinging to exclusive property rights and building paywalls around science objects.
In some ways, the cultural future of science may look a lot like the ancient history of the peoples of Botswana. Their advanced knowledge of their surroundings has sustained them for tens of thousands of years. So too, advances in open science can sustain the global scientific endeavor into the future.
A vision statement for this future academy might be something like this:
We envision an academy where members openly share their most important thoughts, processes, data, and findings through self-governing commons that are intent on the long-term stewardship of resources, on the value of reuse, on the absolute equality of participation, on the freedom of scientific knowledge, and the right of all to participate in discovery, and of each to have their work acknowledged, if not with praise, but with kindness and full consideration.
We are all knowledge hunter-gatherers. Through open repositories, platforms and other cyberinfrastructures we are creating a provident big-data savanna that will nourish science across the globe. Through commoning cyberinfracultures we can teach each other to govern this savanna wisely. Wielding the norms of fierce equality and demand sharing, we can secure this future for all scientists.
And, with enough coffee, I think we might all make it through this day!
Thank you!
This talk was generously supported by the Alfred P. Sloan Foundation
Virtual Democracy 