Neo-proprietarians + Conceptual Obfuscation = To What End?

It's been an interesting/bizarre month with respect to the open source/open access ethos [see disclaimer in 1]. The first part of the month saw two events. One was the posthumous birthday of Aaron Schwartz, and the other was a social media kerfuffle that represents part of a more general conservative backlash to net neutrality [2]. More recently, an article in Nature [3] argued that increases in the number of published papers in recent years (partially enabled by open-access publishers), has diluted the quality-control process enforced through peer-review.

What do these three events have in common? They all involve brushes with neo-proprietarianism, or the advocacy of intellectual property (IP) rights through a simple assumption: private ownership/management of IP is always somehow morally superior to open access. This might range from overzealous prosecutors and politicians to earnest, well-meaning scientists. The result is oddly-placed criticism of ideas that are potentially more beneficial to society than to private owners or firms. At times, people with no direct stake in the IP rights defend the claims of rights holders, which seems odd except in the light of neo-propietarianism (or defending the mere idea of ownership rather than its drawbacks and consequences).

Open Access as Political Rhetoric: Alexis Ohanian's Ad Campaign in support of net neutrality.

In the case of both Aaron Schwartz and the aforementioned Nature article, the issue at hand is open access to scientific articles. The Nature article is well-meaning and raises some good points about how scientists might be compensated for work such as peer review. However, the tone and overall argument is reminiscent of another critique of open access publishing published last year in Science. Furthermore, there are some issues with making a link between publication quantity and the overall quality of the scientific literature. This is particularly true when the argument is made in a Nature article, lest it be interpreted as a conflict of interest [3].

Whether this is simply the act of conflating "the best of the best" with a restrictive paid-access model of publishing or an implicit argument for the infallibility of peer-review elitism is unclear. However, blog posts and data analyses by two biologists (one being Michael Eisen) and a bioinformatician [4, 5, 6] provide a very different (and more nuanced) view of the open-access journal phenomenon. This includes a rebuttal of the argument that the explosion of open-access journals is bad for the quality of the scientific literature and a burden on peer reviewers.

Sometimes quality control is a good thing. This paper was accepted by a so-called "predatory publisher" (maybe you stop bugging me for solicitations to your journal, maybe I won't embarrass you) . In discussions that revolve around publishing "quality" and "prestige", it is common to lump predatory publishers in with all other open-access publishers. Do you need an elite publishing model to prevent things like this from happening? (Answer: a rhetorical "no"). COURTESY: David Mazieres, Eddie Kohler, and Peter Vamplew.

For more reflection on the life of Aaron Schwartz, see this event hosted by the Electronic Freedom Foundation (EFF) called "Hacking for a Better World". And for some less ideonational views on net neutrality, see the two readings on the subject in [7]. Should November be known henceforth as "Open Information Month". In light of this year's events, perhaps.

NOTES:
[1] For purposes of this post, no finer distinctions will be made between true (e.g. the technical definition of) "open access" and Net Neutrality. Particularly as defined by the current debate, Net Neutrality is not equivalent to "open access".

However, for some recent thinking in this area, please see: Godwin, M.   How Wikipedia Zero will serve and promote network neutrality. Mike Godwin's LinkedIn blog, December 1 (2014).

[2] Pendleton, A. and Lannon, B.   One group dominates the second round of net neutrality comments. Sunlight Foundation, December 16 (2014).

[3] Arns, M.   Open accss is tiring out peer reviewers. Nature, 515, 467 (2014).

[4] Taylor, M.   Open-access megajournals reduce the peer-review burden. Sauropod Vertebra Picture of the Week blog, November 27 (2014).

[5] Eisen, M.   Contrary to what you read in Nature, Open Access has not caused the growth in science publishing. It is NOT Junk blog, November 27 (2014).

[6] Saunders, N.   Growth in free and closed scientific publications 2000-2013. Neil Saunders' Rstudio Notebook, November 28 (2014).

[7] Madrigal, A.C. and LaFrance, A.   Net Neutrality: A Guide to (and History of) a Contested Idea. The Atlantic, April 25 (2014) AND Bergstein, B.   Q&A: Lawrence Lessig. MIT Technology Review, October 27 (2014).

Ratchets, Constructions, Games, and Borg in the Reading Queue

Here are a few new (or new to me) papers that are evolution-related from my reading queue. There is a loose theme to these papers (indicated in the title of this post). I will give you my impressions and insights as the post proceeds.

Varieties of uni- and multicellular relationships amongst different species of green algae. COURTESY: Figure 1 in [1].

1. Libby, E. and Ratcliff, W.C.   Ratcheting the Evolution of Multicellularity. Science, 346, 426-427 (2014).

This short paper in a recent issue of Science deals with the transition to multicellularity and associated "ratcheting" mechanisms in what is a complexity theory take on evolutionary transitions and ratchets. According to Libby and Ratcliff's model, the transition to multicellularity involved a transfer of fitness costs from individual cells to groups of cells. This could also be seen as an overall change in the level of selection from individual cells to cell populations [2]. In this case, a so-called ratcheting mechanism is also proposed that provide a mechanism for how such transitions occur. Group living allows for certain group traits to emerge and limits reversion to the single-celled state, a so-called "de-Darwinization" of individual-level cell behaviors [3].

While individual cells transition from being autonomous to being mutually reliant, this occurs only in the context of its fitness effects. For the complexity ratchet to work, there must be opposite effects on fitness. Group living in the form of a colony formation provides a fitness benefit that is not at all present with individualistic cells. Social arrangements such as division of labor can encourage these fitness effects. The authors point to apoptosis as a trait which, while having a high fitness cost to the individual, can be beneficial to the group. Namely, relaxed group selection on apoptosis allows for the growth and nutrient constrains of a population to be circumvented. There are other traits for which individual and group selection differ -- changes in these selective pressures (much like what one would see in a shift to a new environmental niche) are what drive the evolutionary transition.

Do cultural practices (such as dietary innovations) have an influence on human evolution? COURTESY: Frank Stockton, Smithsonian Mag.

2. Laland, K.N., Odling-Smee, J., and Myles, S.   How culture shaped the human genome: bringing genetics and the human sciences together. Nature Review Genetics, 11, 137-148 (2010).

Transitions to group living also involve new sources of fitness costs, distinct from those that exist at the individual level. In this lengthy review article (from 2010), Laland, Odling-Smee, and Myles argue that culture can modify fitness costs for a given trait. The article authors are also advocates of niche construction theory and a post-synthesis evolutionary theory [4], which is clearly seen in their treatment of how culture interfaces with evolution. The mediating effects of culture on population genomics and evolutionary dynamics can be seen in gene-culture coevolution, but also suggests that there is another dimension to group selection in animal species that possess culture. These authors might also argue that cultural selection pressure is a key factor in human uniqueness, something we will come back to in the next section.

While the examples given in the article are muddied with more standard environmental selection pressures, the argument for cultural selection is that some environmental pressures are specifically related to cultural construction [5]. For example, natural selection due to dietary practices are reinforced by human modification of the environment (e.g. harvesting animal milk for general consumption). While genes and culture are viewed as interacting forms of inheritance, it is not so clear as to how they can be disentangled. In cases where cultural boundaries shape population genetics, the answer is relatively easy. However, in cases where cultural dynamics influence the frequency of host-pathogen interactions or heat shock genes, removing the signal from the noise is less clear.

Chimps playing the Prisoner's Dilemma. COURTESY: Science Magazine.

3. Martin, C.F., Bhui, R., Bossaerts, P., Matsuzawa, T., and Camerer, C.   Chimpanzee choice rates in competitive games match equilibrium game theory predictions. Scientific Reports, 4, 5182 doi:10.1038/srep05182 (2014).

3a. Lopata, J.   How Star Trek may show the emergence of human consciousness. Nautil.us, November 18 (2014).

3b. Helbing, D., Yu, W., Opp, K-D., and Rauhut, H.   Conditions for the Emergence of Shared Norms in Populations with Incompatible Preferences. PLoS One, 9(8), e104207 doi:10.1371/ journal.pone. 0104207 (2014).

Here is an interesting collection of readings, which make sense in the context of the Martin et.al paper. In Martin et.al, the authors compare equilibrium expectations for Prisoner's Dilemma (PD) game [6] play with actual outcomes for both humans and chimps. It was found that when chimps play the game, the result is closer to the theoretical expectation than when humans play the game. This suggests that chimpanzee decision-making is more homogeneous than human decision-making, at least in the context of interactions that involve theory of mind. While the result is curious, there are two more recent items that might provide useful speculation about these outcomes.

In a recent article published in Nautil.us (3a), it is postulated that early human cognition (and perhaps cognition in the human-chimp common ancestor) resembled that of the Borg from Star Trek. It is argued that our ancestors were Borg-like in their ability exhibit little individuality across populations. In terms of the PD game, the theoretical equilibria often results from a convergence upon pure strategies. This may not so much a improvement upon an individual's ability to predict what their opponent will do next as the lack of heterogeneity in behavior over time. Thus, a species that exhibits much heterogeneity with respect to behavioral innovation (e.g. humans) would deviate from the theoretical expectation [7].

But does that mean the PD model is not really valuable in modeling human behavior? After all, the original formulation was modeled on human behavior. In addition, the model implicitly relies upon behavioral traits possibly unique to human cognition (such as theory of mind). In 3b, we can see that even though humans have a great diversity of preferences, sets of shared norms may emerge that serve to unify the behavioral outcomes of a population [8]. Despite our great individuality, some aspects of human culture can serve to reduce human heterogeneity.

We were a bit like the Borg (sans hive mind-style collective consciousness), once... COURTESY: Star Trek Online Pictures.

NOTES:
[1] Michod, R.E.   Evolution of individuality during the transition from unicellular to multicellular life. PNAS, 104(S1), 8613-8618 (2007).

[2] Of course, there is plenty of debate regarding the role of group and multilevel selection in the evolutionary process. For more on the virtues of these types of selection, please see: Traulsen, A. and Nowak, M.A.   Evolution of cooperation by multilevel selection. PNAS, 103(29), 10952–10955 (2006) AND Goodnight, C.J.   Multilevel selection: the evolution of cooperation in non-kin groups. Population Ecology, 47, 3-12 (2005).

[3] The term "de-Darwinization" refers to the relaxation of selection for a given trait or level of selection. Please see: Godfrey-Smith, P.   Darwinian Populations and Natural Selection. Oxford University Press, New York (2009).

[4] Laland, K., Uller, T., Feldman, M., Sterelny, K., Muller, G.B., Moczek, A., Jablonka, E., Odling-Smee, J., Wray, G.A., Hoekstra, H.E., Futuyma, D.J., Lenski, R.E., Mackay, T.F.C., Schluter, D., and Strassmann, J.E.   Does evolutionary theory need a rethink? Nature, October 8 (2014).

[5] Richerson, P.J. and Boyd, R.   Natural Selection and Culture. BioScience, 34(7), 430-434 (1984) AND Bell, A.V.   Why cultural and genetic group selection are unequal partners in the evolution of human behavior. Communicative and Integrative Biology, 3(2), 159–161 (2010).

[6] Johnson, D.D.P., Stopka, P., and Bell, J.   Individual variation evades the Prisoner's Dilemma. BMC Evolutionary Biology, 2, 15 (2002).

[7] Herbert-Read, J.E., Krause, S., Morrell, L.J., Schaerf, T.M., Krause, J., and Ward, A.J.W.   The role of individuality in collective group movement. Proceedings of the Royal Society B, 280(1752), 1-8 (2013).

[8] Such norms, such as sharing, exhibit species differences in children. For an example, please see: Hamann, K., Warneken, F., Greenberg, J.R., and Tomasello, M.   Collaboration encourages equal sharing in children but not in chimpanzees. Nature 476, 328–331 (2011).

Thought (Memetic) Soup: November edition

This content is cross-posted to Tumbld Thoughts. Here are a few short observations on the state of the world and data, circa Summer 2014. Haven't gotten around to cross-posting these yet. The meta-theme is social disruption, evolutionary change, and economic dynamics, in spite of ideonational bias. These include Disruption du jour (I), Satire Makes it Doubly Skewed (II), and Ideonational Skew - Satire = Epistemic Closure? (III).

I. Disruption du jour

Is the idea of disruptive innovation a useful concept, or is it largely a misapplied buzzword. In the original definition of "creative destruction", Joseph Schumpeter described a process of innovation that resembled an avalanche or an earthquake. For example, most innovations do not reshape their respective industries, but a few key innovations (born out of creative ferment) do.

The modern notion of disruptive innovation does not make the distinction between the effects of innovation in different industries, nor are all so-called "disruptions" equally as valuable. Schumpeter's model of disruptive innovation resembles a power law, while the modern conception of disruptive innovation argues that transformative changes are ubiquitous. Here are some readings on the myth and controversies surrounding the concept:

Lepore, J.   The Disruption Machine. New Yorker, June 23 (2014).

* a critique of the "disruption" industry.

Bennett, D.   The Innovator's New Clothes: Is Disruption a Failed Model? Bloomberg Businessweek, June 18 (2014).

* perhaps Lepore is right -- disruption for disruption's sake is not a viable model of economic change.

Bennett, D.   Clayton Christensen Responds to New Yorker Takedown of 'Disruptive Innovation'. Bloomberg Businessweek, June 20 (2014).


* a rebuttal to the Lepore article from the modern "disruption" guru.

II. Satire Makes it Doubly Skewed

Two (intentionally) skewed views on Evolution [1, 2]: God does not do art, and monkeys still exist. Or something like that. Anyways, here is a sampling of creationism satire from Summer 2014.

[1] Pliny the In-Between   Theistic evolution. Evolving Perspectives blog, July (2014).

[2] Why There are Still Monkey (fake book in the Dummies series). Timothy McVeins Twitter post, June 20 (2014).

III. Ideonational Skew - Satire = Epistemic Closure?

Statistical conspiracy theory? Here is a link to John Williams' Shadowstats site and (appropriately) three readings [1-3] that critique the overall approach. For example, in one reading, it is suggested that the "shadow" in the Shadowstats name consists of an inappropriate modeling methodology.

[1] Aziz   The Trouble with Shadowstats. Azizonomics, June 1 (2013).

[2] Krugman, P.   Always Inflation Somewhere. Conscience of a Liberal blog, July 19 (2014).

[3] Hiltzik, M.   A new right-wing claim: Obama must be lying about inflation. The Economy Hub, Los Angeles Times, July 23 (2014).

The Top 100 Needles in a Haystack

A week or so ago, Nature News published a feature on the Top 100 (e.g. most-cited) articles of all time [1]. Interesting read, even if you don't agree with their methods or conclusions. Briefly, a Science Citation Index (SCI) was used to generate a list, the top 100 articles of which were considered the most highly-cited papers. Another more inclusive list was generated for comparison using Google Scholar. The outcomes were then evaluated.

The top papers-as-mountain peak analogy. COURTESY: Nature Publishing.

So which type of papers dominated the top of the list? As you might have guessed, papers that describe the details of a now-ubiquitous method dominate the top 100. Articles on methods such as single-step RNA isolation (#5) or density-functional thermochemistry (#8) have been cited in the neighborhood of 50-60,000 times because they provide a simple description of a method that has now become widespread. As it is considered good form to cite the source article for a given method, these are the top articles in this index. It may seem a bit disingenuous to count these articles as the most influential in science. For example, the Watson and Crick paper [3] describing the structure of DNA does not make the top 100. But, this methodology allows us to see the relative diffusion of such methods in the literature. Normalizing the number of citations by their respective age gives us a citation rate, which in turn allows us to estimate the velocity [4] of a given method through the scientific community.

Number 12 on the list is the paper that introduced the BLAST genome alignment method [2]. COURTESY: Nature Publishing.

For comparative purposes, the Nature News article also provides an alternate index, one compiled by Google Scholar. This index not only includes books, but deals with citations that are more conceptual in nature. For example, the top 100 citations of all time includes: Thomas Kuhn's "Structure of Scientific Revolutions" (#7), Claude Shannon's "Mathematical Theory of Communication" (#9), Rogers' "Diffusion of Innovations" (#17), "The Rat Brain in Stereotaxic Coordinates" (#23), and Zadeh's "Fuzzy Sets" (#29). Much like the SCI method, the Google Scholar method results in a long-tailed distribution, with a few papers far exceeding the rest of the literature in terms of citations. While it is less dominated by methods papers (and books), most of the top references on the list have nevertheless had a major influence on a number of fields. 

But what does all this mean for your recent publication? Will your recent paper on the mathematical structure of inter-neuronal conversion be worthy of one of these top spots at some point in the future? One interesting exercise might be to predict the future citation rates and diffusion velocities for recent papers and books (published within the last 10 years). While not at the very top of the list, these papers would demonstrate how the middle of the distribution lives. And for all of those papers with only a few citations even after years of being published, don't despair. It could be that your paper does not fit the criterion of a "top" paper (e.g. covers a series of clever but non-landmark studies), and so has not gained a high profile. Citation patterns are a curious thing.

NOTES:
[1] The relevant databases have limited this to the 20th and 21st centuries. Article citation: Van Noorden, R., Maher, B., Nuzzo, R.   The Top 100 Papers. Nature News, October 29 (2014).

[2] Full citation: Altschul, S.F., Gish, W., Miller, W., Myers, E.W., and Lipman, D.J.   Basic local search alignment tool. Journal of Molecular Biology, 215, 403-410 (1990).

[3] Watson, J.D. and Crick, F.H.C.   A Structure for Deoxyribose Nucleic Acid. Nature, 171, 737-738 (1953).

[4] Calculating method or publication "velocity" involves mapping the citation rate (per unit time) to a metric space or graph the represent the "shape" of the scientific community (disciplines, interest areas, etc). This is intentionally vague, as various community shapes are contingent on many factors.