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{ "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": "2017-01-01T18:00:00Z", "render_galley": null, "galleys": [ { "label": "PDF", "type": "pdf", "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26986/galley/16622/download/" } ] }