The Sapir‐Whorf hypothesis and inference under uncertainty
Copyright policy )The Sapir‐Whorf hypothesis and inference under uncertainty
The Sapir‐Whorf hypothesis holds that human thought is shaped by language, leading speakers of different languages to think differently. This hypothesis has sparked both enthusiasm and controversy, but despite its prominence it has only occasionally been addressed in computational terms. Recent developments support a view of the Sapir‐Whorf hypothesis in terms of probabilistic inference. This view may resolve some of the controversy surrounding the Sapir‐Whorf hypothesis, and may help to normalize the hypothesis by linking it to established principles that also explain other phenomena. On this view, effects of language on nonlinguistic cognition or perception reflect standard principles of inference under uncertainty. WIREs Cogn Sci 2017, 8:e1440. doi: 10.1002/wcs.1440This article is categorized under: Linguistics > Computational Models of Language Linguistics > Language in Mind and Brain
- University of California, Berkely United States
- University of California United States
- California Digital Library United States
- University of California United States
- Department of Linguistics University of California United States
Models, Statistical, Biomedical and Clinical Sciences, Biological Psychology, Neurosciences, Uncertainty, Statistical, Thinking, Cognition, Models, Psychology, Biological psychology, Humans, Cognitive Sciences, Cognitive and Computational Psychology, Cognitive and computational psychology, Color Perception, Language
Models, Statistical, Biomedical and Clinical Sciences, Biological Psychology, Neurosciences, Uncertainty, Statistical, Thinking, Cognition, Models, Psychology, Biological psychology, Humans, Cognitive Sciences, Cognitive and Computational Psychology, Cognitive and computational psychology, Color Perception, Language
selected citations These citations are derived from selected sources.This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).37 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
Citations provided by BIP!Popularity provided by BIP!