DE eng

Search in the Catalogues and Directories

Page: 1 2
Hits 1 – 20 of 31

1
The influence of animacy on perspective-taking and word order during language production ...
Brough, Jessica. - : Open Science Framework, 2022
BASE
Show details
2
Boundaries in space and time: Iconic biases across modalities
In: ISSN: 0010-0277 ; EISSN: 1873-7838 ; Cognition ; https://hal.archives-ouvertes.fr/hal-03408801 ; Cognition, Elsevier, 2021, 210, pp.104596. ⟨10.1016/j.cognition.2021.104596⟩ (2021)
BASE
Show details
3
Boundaries in space and time: Iconic biases across modalities
In: ISSN: 0010-0277 ; EISSN: 1873-7838 ; Cognition ; https://hal.archives-ouvertes.fr/hal-03509748 ; Cognition, Elsevier, 2021, 210, pp.104596. ⟨10.1016/j.cognition.2021.104596⟩ (2021)
BASE
Show details
4
Children and Adults Use Linguistic Cues To Inform Pedagogical Preferences ...
Bashyam, Sharanya. - : University of Chicago, 2021
BASE
Show details
5
Vocalic Intrusions in Consonant Clusters in Child-Directed vs. Adult-Directed Speech ...
Garmann, Nina Gram; Hansen, Pernille; Simonsen, Hanne Gram. - : Apollo - University of Cambridge Repository, 2021
BASE
Show details
6
Using narrative to manipulate perceived mind and word order during language production ...
Brough, Jessica. - : Open Science Framework, 2021
BASE
Show details
7
Improving Multilingual Models for the Swedish Language : Exploring CrossLingual Transferability and Stereotypical Biases
Katsarou, Styliani. - : KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021
BASE
Show details
8
Vocalic Intrusions in Consonant Clusters in Child-Directed vs. Adult-Directed Speech
Garmann, Nina Gram; Hansen, Pernille; Simonsen, Hanne Gram. - : Frontiers Media S.A., 2021. : Frontiers in Psychology, 2021
BASE
Show details
9
Positive AI with Social Commonsense Models
Sap, Maarten. - 2021
BASE
Show details
10
Production and Substantive Bias in Phonological Learning
In: Proceedings of the Annual Meetings on Phonology; Proceedings of the 2020 Annual Meeting on Phonology ; 2377-3324 (2021)
BASE
Show details
11
A learning bias for word order harmony: evidence from speakers of non-harmonic languages
In: ISSN: 0010-0277 ; Cognition, Vol. 204 (2020) P. 104392 (2020)
BASE
Show details
12
Processing of novel grammatical features during real-time second language production and comprehension
Gardner, Qingyuan Liu. - : The University of Edinburgh, 2020
BASE
Show details
13
Policy recommendations for language learning: Linguists’ contributions between scholarly debates and pseudoscience
In: Journal of the European Second Language Association; Vol 3, No 1 (2019); 1–11 ; 2399-9101 (2019)
BASE
Show details
14
Social Cues, Social Biases: Stereotypes in Annotations on People Images
In: Proceedings of the AAAI Conference on Human Computation and Crowdsourcing; Vol. 6 No. 1 (2018): Sixth AAAI Conference on Human Computation and Crowdsourcing (2018)
BASE
Show details
15
When extremists win: cultural transmission via iterated learning when populations are heterogeneous
Kary, A.; Perfors, A.; Brown, S.D.. - : Wiley; Congitive Science Society, 2018
BASE
Show details
16
Gender biases and linguistic sexism in political communication: A comparison of press news about men and women Italian ministers ...
Sensales, Gilda; Areni, Alessandra. - : PsychOpen GOLD, 2017
BASE
Show details
17
Verb Learning Under Guidance ...
He, Xiaoxue Angela. - : Digital Repository at the University of Maryland, 2015
BASE
Show details
18
Inductive evolution: cognition, culture, and regularity in language
Ferdinand, Vanessa Anne. - : The University of Edinburgh, 2015
Abstract: Cultural artifacts, such as language, survive and replicate by passing from mind to mind. Cultural evolution always proceeds by an inductive process, where behaviors are never directly copied, but reverse engineered by the cognitive mechanisms involved in learning and production. I will refer to this type of evolutionary change as inductive evolution and explain how this represents a broader class of evolutionary processes that can include both neutral and selective evolution. This thesis takes a mechanistic approach to understanding the forces of evolution underlying change in culture over time, where the mechanisms of change are sought within human cognition. I define culture as anything that replicates by passing through a cognitive system and take language as a premier example of culture, because of the wealth of knowledge about linguistic behaviors (external language) and its cognitive processing mechanisms (internal language). Mainstream cultural evolution theories related to social learning and social transmission of information define culture ideationally, as the subset of socially-acquired information in cognition that affects behaviors. Their goal is to explain behaviors with culture and avoid circularity by defining behaviors as markedly not part of culture. I take a reductionistic approach and argue that all there is to culture is brain states and behaviors, and further, that a complete explanation of the forces of cultural change can not be explained by a subset of cognition related to social learning, but necessarily involves domain-general mechanisms, because cognition is an integrated system. Such an approach should decompose culture into its constituent parts and explore 1) how brains states effect behavior, 2) how behavior effects brain states, and 3) how brain states and behaviors change over time when they are linked up in a process of cultural transmission, where one person's behavior is the input to another. I conduct several psychological experiments on frequency learning with adult learners and describe the behavioral biases that alter the frequencies of linguistic variants over time. I also fit probabilistic models of cognition to participant data to understand the inductive biases at play during linguistic frequency learning. Using these inductive and behavioral biases, I infer a Markov model over my empirical data to extrapolate participants' behavior forward in cultural evolutionary time and determine equivalences (and divergences) between inductive evolution and standard models from population genetics. As a key divergence point, I introduce the concept of non-binomial cultural drift, argue that this is a rampant form of neutral evolution in culture, and empirically demonstrate that probability matching is one such inductive mechanism that results in non-binomial cultural drift. I argue further that all inductive problems involving representativeness are potential drivers of neutral evolution unique to cultural systems. I also explore deviations from probability matching and describe non-neutral evolution due to inductive regularization biases in a linguistic and non-linguistic domain. Here, I offer a new take on an old debate about the domain-specificity vs -generality of the cognitive mechanisms involved in language processing, and show that the evolution of regularity in language cannot be predicted in isolation from the general cognitive mechanisms involved in frequency learning. Using my empirical data on regularization vs probability matching, I demonstrate how the use of appropriate non-binomial null hypotheses offers us greater precision in determining the strength of selective forces in cultural evolution.
Keyword: cognitive biases; cognitive modelling; cultural evolution; frequency learning; language evolution
URL: http://hdl.handle.net/1842/11741
BASE
Hide details
19
Verb Learning Under Guidance
BASE
Show details
20
Biased generalization of newly learned phonological alternations by 12-month-old infants
In: Cognition , 133 (1) 85 - 90. (2014) (2014)
BASE
Show details

Page: 1 2

Catalogues
0
0
0
0
0
0
0
Bibliographies
0
0
0
0
0
0
0
0
0
Linked Open Data catalogues
0
Online resources
0
0
0
0
Open access documents
31
0
0
0
0
© 2013 - 2024 Lin|gu|is|tik | Imprint | Privacy Policy | Datenschutzeinstellungen ändern