[{"id":234,"title":"How to Build a Global Tree of All Known Languages? - A Brief Demonstration.","sha":"138279e18ac6c0cb44da84e51e1b37df","user_id":null,"state":"published","body":"[I] (https://unive-paris1.academia.edu/JuliendHuy) used the [Dedius’s binary coding (with MrBayes)] (http://rspb.royalsocietypublishing.org/content/royprsb/suppl/2010/08/27/rspb.2010.1595.DC1/rspb20101595supp1.pdf) of the [WALS dataset] (http://wals.info/), the softwares [Structure 2.3.4]  (http://pritchardlab.stanford.edu/structure.html) (fig.1, see supplementary material), and [StructureHarvester] (http://taylor0.biology.ucla.edu/structureHarvester/) (fig.2) to estimate the most likelihood number (“K”) of founding populations (here, K = 20) needed to explain the structure of the corpus. For each cultural area, the Fst score oscillates between 42–88%, [which is much higher than the genetic variation among human populations] (http://www.pnas.org/content/106/42/17671.short), and suggests that the language families, once established, seem to have been very conservative.  Then I excluded from the corpus each language with more than 30% data which refer to acculturation signal (i.e. less than 70% of single-origin). Indeed, these languages having a complex history, it is expected that they are intermediate between many others and “blur” the phylogenetic signal. Using the altered corpus, I created many trees and networks (fig.3-5), which correctly group, for the first time, all languages into known language families and show evidence for some higher level clusters. The Austronesian language family may not form a monophyletic group.   \r\nThis idea, which has yet to be tested in larger datasets, may be a major step toward a complete understanding of the historical relationship between the world's languages and many other important questions, such as the reconstruction of the human proto-language's structure and its evolution. ","created_at":"2015-09-21T22:04:44.258Z","updated_at":"2016-05-14T05:22:13.934Z","zenodo_id":62024,"doi":"http://dx.doi.org/10.5281/zenodo.31290","subject":null,"tags":["phylogenetics","language","structure","global tree of all known languages","prehistory","proto-language","comparative method","cultural fst","cultural evolution","linguistic evolution","networks","linguistics","evolutionary anthropology","origin of language","mother tongue","first language","journal of brief ideas"],"vote_count":2,"view_count":1,"score":2.1,"deleted":false,"muted":false,"tweeted":true,"attachment_file_name":"Electronic_supplementary_material.pdf","attachment_content_type":"application/pdf","attachment_file_size":292814,"attachment_updated_at":"2015-09-21T22:04:41.148Z"},{"id":349,"title":"Playing Games with Ideas: when epistemology pays off","sha":"e4702f43c1c9f3561e57b3ab001a924b","user_id":null,"state":"published","body":"In standard game theory analysis, gameplay proceeds using rational strategies. While there is no explicit link between rationality and strategy selection, playing to equilibrium solutions often depends on choosing the optimal strategy. Yet what if strategy optimality is not obvious to the players? Often, people make seemingly irrational decisions based on beliefs or situational interpretations of the empirical world. These beliefs have high social import, but with little advantage compared to empirical reality. \r\n\r\nWe use a decision kernel to model how beliefs (an epistemological network) influence a rational strategy suite (top box in attachment). The feedforward network output is a set of beliefs that influence gameplay as a set of rational behavior (empirical strategy suite). This results in an epistemological-influenced social capital payoff function, and an empirical payoff function (bottom box in attachment). The joint distribution (or area of intersection between the payoff functions) is the epistemological payoff. This epistemological payoff can be small (low conditional social payoff) or large (high conditional social payoff). When small, players play their strategies close to the optimal expectation. Larger epistemological payoffs result plays that have with relatively higher social utility, but also little immediate utility when compared to the empirical world.","created_at":"2016-11-21T06:06:01.489Z","updated_at":"2016-11-21T11:38:15.392Z","zenodo_id":167647,"doi":"https://doi.org/10.5281/zenodo.167647","subject":null,"tags":["cognition","game theory","cultural evolution","complex systems","theory","philosophy"],"vote_count":1,"view_count":1,"score":1.1,"deleted":false,"muted":false,"tweeted":true,"attachment_file_name":"whole-figure.png","attachment_content_type":"image/png","attachment_file_size":286497,"attachment_updated_at":"2016-11-21T06:06:01.443Z"}]