MétaCan
Menu
Back to cohort
Record W2894593830 · doi:10.1177/0956797618795471

Link Between Facial Identity and Expression Abilities Suggestive of Origins of Face Impairments in Autism: Support for the Social-Motivation Hypothesis

2018· article· en· W2894593830 on OpenAlexafffund
İpek Oruç, Fakhri Shafai, Grace Iarocci

Bibliographic record

VenuePsychological Science · 2018
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsSimon Fraser UniversityUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsPsychologyAutismExpression (computer science)Autism spectrum disorderIdentity (music)Facial expressionFace (sociological concept)Face perceptionDevelopmental psychologySocial identity approachCognitive psychologyPopulationSocial identity theorySocial groupSocial psychologyCommunicationNeurosciencePerceptionLinguistics

Abstract

fetched live from OpenAlex

Individuals with autism spectrum disorder (ASD) often have difficulties with processing identity and expression in faces. This is at odds with influential models of face processing that propose separate neural pathways for the identity and expression domains. The social-motivation hypothesis of ASD posits a lack of visual experience with faces as the root cause of face impairments in autism. A direct prediction is that identity and expression abilities should be related in ASD, reflecting the common origin of face impairment in this population. We tested adults with and without ASD ( ns = 34) in identity and expression tasks. Our results showed that performance in the two domains was significantly correlated in the ASD group but not in the comparison group. These results suggest that the most likely origin for face impairments in ASD stems from the input stage impacting development of identity and expression domains alike, consistent with the social-motivation hypothesis.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.600
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.132
GPT teacher head0.426
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations14
Published2018
Admission routes2
Has abstractyes

Explore more

Same venuePsychological ScienceSame topicAutism Spectrum Disorder ResearchFrench-language works237,207