The Way of The Polymath

This content is cross-posted to the Orthogonal Research and Education Lab Medium.

What constitutes a polymath, and why are they so rare? Another way to ask this question is why are there so few foxes relative to hedgehogs? The occasional hyper-specialist would have you believe the term "polymath" is an epithet. However, there are a number of skills that the polymath possesses that translate into an advantage for advancing both theory and fundamental knowledge. Aside from the mastery of multiple intellectual areas, the most important of these is the ability to synthesize information from a number of sources. The advent of digital scholarship may enable this ability in the foxes among us [1].

One depiction (late 19th, early 20th century) of a polymath.

Back in 2015, Nature Careers released a list of recommendations to combat the hyper-specialist tendencies of PhD programs [2], but many of these are simply window-dressing. One view is that improving the state of interdisciplinary thinking is to improve the infrastructure for collaboration and disseminating big ideas. However, a more fundamental (and harder-to- implement) change that can be made is to reconfigure the epistemic landscape of science [3]. One aspect of this indeed involves the training of scientific generalists, but generalist training does not equate polymathism.


The other factor involves the potential zero-sum nature of generalized knowledge [4]. There is a constant tradeoff between deep expertise in one area versus more shallow expertise in a number of areas simultaneously. Society tends to reward deep expertise, and synthesis is rather expensive knowledge-wise. In any case, there is a game-theoretic interpretation of this scenario, but that is a topic for another post.  

Here is a semi-annotated reading list on singular (but multidisciplinary) academic activity:

Hossenfelder, S.   The loneliness of my notepad. Backreaction blog, July 8 (2015).


Issacson, W.   Myth of the Lone Genius. Aspen Journal of Ideas, July 24 (2015). 

These articles critically examine the myth of the lone genius. The first article points out that tools enabling collaboration (e.g. internet, large-scale consortia) are finally starting to bear fruit. Proportion of single-author papers has gone down over last 20-30 years, but that does not mean lone efforts are in absolute decline. In fact, "isolation" is a myth, given the social networks and information-sharing culture in academia.


Bateman, T.S. and Hess, A.M.   Different personal propensities among scientists relate to deeper vs. broader knowledge contributions. PNAS, 112(12), 3653-3658. (2015).


Kirkegaard, E.   Personality correlates of breadth vs. depth of research scholarship. Project Polymath blog, March 6 (2015).

* relates style of scientific investigation to type of contributions (specialized studies vs. broad interdisciplinary synthesis) made by scientists. Survey methodology does not assume that contributions can be both deep and broad, despite setting this up as a dichotomy. Is "deeper" vs. "broader" a major dichotomy in scientific exploration.

* suggests that the difference between scientific generalists and specialists is epistemic, not economic as traditionally assumed (e.g. a certain strategy is more or less risky).

* views differences in types of scientists (e.g. polymathy) as a matter of personality, not epistemic bias.


Palla, G., Tibely, G., Mones, E., Pollner, P., and Vicsek, T.   Hierarchical networks of scientific journals. arXiv, 1506.05661 (2015).

Presents a hierarchical network analysis of scientific journals and their relevance to measuring influence and the diffusion of ideas in specific scientific fields.


Muldoon, R. and Weisberg, M.  Robustness and idealization in models of cognitive labor. Synthese, 183, 161-174 (2011).

* introduce us to an economic optimization model called the marginal contribution/reward (MCR).

* motivation of individuals or groups of scientists is accomplished either through self-interest or epistemic norms.

* MCR assumes that cognitive labor can be optimally distributed across collaborations to solve hard problems. The problem is stated as a constrained maximization of "success" and "return". Model does not provide good approximations of success, return, or epistemic norms, not does it distinguish amongst different scientific skill-sets (generalists vs. specialists vs. hyper-specialists).


Sarma, G.P.   Should we train scientific generalists? arXiv, 1410.4422 (2014).

* how to introduce students to a vocabulary of multiple disciplines, and how this would encourage research breadth.

alexarje   Disciplinarities: intra, cross, multi, inter, trans. Alexander Refsum Jensenius blog, March 12. (2012).

NOTES:
[1] Alicea, B.   "Academic Connectivity and the Future of Scientific Ideas". Synthetic Daisies blog, September 9 (2011).

[2] Nurse, P.   To build a scientist. Nature, 523, 371-373 (2015).

[3] Weisberg, M. and Muldoon, R.   Epistemic Landscapes and the Division of Cognitive Labor. Philosophy of Science, 76(2), 225-252 (2009).

[4] Downey, G.   Interdisciplinarity, sub-disciplinarity, and inter-topicality. Uncovering Information Labor blog, March 31 (2006).

Assorted Darwin Day Content

For this year's Darwin Day post, I will highlight a number of items I have recently run across on Twitter. Some of these have been retweeted on the Orthogonal Research and Education Lab Twitter feed, other materials are related to discussions in our research group meetings.

To start things off, I will draw your attention to a new special issue of Royal Society of London B called "Basal cognition: multicellularity, neurons and the cognitive lens" that is worth checking out. The term "basal" refers to evolutionary origins in the context of phylogeny (the tree of life). 

There are three papers of particular note for Darwin Day: "The chemical brain hypothesis for the origin of nervous systems" by Gaspar Jekely, "Elementary Nervous Systems" by Detlev Arendt, and "Uncovering cognitive similarities and differences, conservation and innovation" by Michael Levin and colleagues.

The new paper on elementary nervous systems in Royal Society B (click to enlarge, figure from paper). COURTESY: Detlev Arendt.

A pointer to the Darwin Online repository.

In terms of old drawings and other archival materials, check out the Darwin Online project. This is a nice repository of Darwin-related historical and scientific works. This resource contains books, personal correspondence, and published materials. Speaking of history, let's turn to the deep history of life.....

A billion years of continental drift as an animated gif. Click to enlarge.

This next feature is a new paper on a billion years of plate tectonic dynamics: "Extending full-plate tectonic models into deep time: Linking the Neoproterozoic and the Phanerozoic" by Mike Tetley and colleagues. Now published in Earth Science Reviews, it is something we recently discussed in the weekly DevoWorm group meeting.

Following up on the DevoWorm discussion, which was about mapping the continental drift animation to the most basal branches of the tree of life, is an attempt to map Mammalian phylogeny [1] to continental drift over the past 225 million years. This was created by Carlos E. Alvarez. The numbers on the maps (top) correspond to the numbered clades (subtrees - bottom). This topic deserves a deeper dive into the latest Phylogeography research [2], which may be the subject of a future blog spot.

An attempt at matching up the tree of life with continental drift (click to enlarge). COURTESY: Carlos E. Alvarez

The next feature is a new paper on evolution of development (evo-devo) in nervous system anatomy called "Evolution of new cell types at the lateral neural border", now published in Current Topics in Developmental Biology. This study even uses converging evidence from genetic regulatory networks and anatomy to demonstrate common mechanisms shared between invertebrates and vertebrates.

A new paper on the evolution of new neuronal cell types (click to enlarge). COURTESY: Jan Stundl (Caltech).

Not only is this Darwin Day, but also the 50th anniversary of a Nature paper by Kimura and Ohta [3] on the Neutral Theory of Molecular Evolution. Neutral Theory postulates that most biological variation is expressed in selectively neutral genes, and so is random in nature [4]. This stands in opposition to the selectionist perspective of evolutionary change [5, 6].

Fully-tweetable neutral theory of evolution. COURTESY: Andrew J. Crawford.

Finally, and returning to neuroevolution, there are several items of interest from the laboratory of Cassandra Extavour. The first is a talk at the Society of Integrative and Comparative Biology meeting on the evo-devo-eco-neuro-biology of Drosophila learning and memory. For more evo-devo work from Dr. Extavour's lab, check out this recent work (with open data) on insect size and shape [7, 8].

Original artwork from SICB Twitter Account, commentary from Ken A. Field.

Hand-drawn notes on the SICB plenary talk. COURTESY: Dr. Ajna Rivera.

NOTES:

[1] Foley N.M., Springer M.S. and Teeling E.C. (2016). Mammal madness: is the mammal tree of life not yet resolved? Philosophical Transactions of the Royal Society B, 37120150140. doi:10.1098/ rstb.2015.0140.

[2] Avise, J.C. (2000). Phylogeography: the history and formation of species. Harvard University Press, Cambridge, MA.

[3] Kimura, M. and Ohta, T. (1971). Protein Polymorphism as a Phase of Molecular Evolution. Nature, 229, 467–469.

[4] Kimura, M. (1983). The Neutral Theory of Molecular Evolution. Cambridge University Press, Cambridge, UK.

[5] Nei, M. (2005). Selectionism and Neutralism in Molecular Evolution. Molecular Biology and Evolution, 22(12), 2318–2342. doi:10.1093/molbev/msi242.

[6] There are other critiques of selectionism from other perspectives. Here is one in the area of brain function: Fernando, C., Szathmary, E., and Husbands, P. (2012). Selectionist and Evolutionary Approaches to Brain Function: A Critical Appraisal. Frontiers in Computational Neuroscience, 6, 24. doi:10.3389/ fncom.2012.00024.

[7] Church, S.H., Donoughe, S., de Medeiros, B.A.S., and Extavour, C.G. (2019). Insect egg size and shape evolve with ecology but not developmental rate. Nature, 571, 58–62.

[8] Church, S.H., Donoughe, S., de Medeiros, B.A.S., and Extavour, C.G. (2019). A dataset of egg size and shape from more than 6,700 insect species. Scientific Data, 6, 104.