{"pk":26986,"title":"Population size, learning, and innovation determine linguistic complexity","subtitle":null,"abstract":"There are a number of claims regarding why linguistic com-plexity varies, for example: i) different types of societalstructure (e.g. Wray & Grace, 2007), ii) population size (e.g.Lupyan & Dale, 2010), and iii) the proportion of child vs. adultlearners (e.g. Trudgill, 2011). This simple model of interact-ing agents, capable of learning and innovation, partially sup-ports all these accounts. However, several subtle points arise.Firstly, differences in the capacity or opportunity to learn deter-mine how much complexity can remain stable. Secondly, smallpopulations are susceptible to large amounts of drift and sub-sequent loss, unless innovation is frequent. Conversely, largepopulations remain resilient to change unless there is too muchinnovation, which leads to a collapse in complexity. Next, ifadult learners are prevalent, we can instead expect less sus-tained complexity in large populations. Finally, creolisationdoes not imply simplification in smaller populations.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[{"word":"linguistic complexity; language variation; innova-tion; social networks; agent-based models; cultural evolution."}],"section":"Talks: Papers","is_remote":true,"remote_url":"https://escholarship.org/uc/item/3x3355t4","frozenauthors":[{"first_name":"Matthew","middle_name":"","last_name":"Spike","name_suffix":"","institution":"The Australian National University","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"2017-01-01T10:00:00-08:00","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/26986/galley/16622/download/"}]}