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Record W2900502844 · doi:10.6000/1929-4409.2018.07.19

Autism Spectrum Disorder and Harassment: An Application of Attribution Theory

2018· article· en· W2900502844 on OpenAlexvenueno aff
Melanie Clark Mogavero, Ko‐Hsin Hsu

Bibliographic record

VenueInternational Journal of Criminology and Sociology · 2018
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsnot available
Fundersnot available
KeywordsAttributionPsychologyAutism spectrum disorderAutismPunishment (psychology)Punitive damagesAttribution biasSocial psychologySocial information processingDevelopmental psychologyPsychiatry

Abstract

fetched live from OpenAlex

The social and communication impairments among those with autism spectrum disorder (ASD) may result in some unknowingly harassing someone while pursuing a romantic interest. Weiner’s (1974) Attribution Theory suggests that when people attribute negative behaviors to a condition, they perceive less controllability, and evoke fewer negative emotions and punishments. The authors applied Attribution Theory using a sample of 545 undergraduates who received one of three vignettes depicting a male harassing a female romantic interest (no mention of ASD, mention of ASD, mention of ASD and difficulty with social relationships and communication). Those who received the vignettes that mentioned the perpetrator had ASD perceived the behavior as less controllable and fewer supported punishment. The results demonstrate support for disclosing one’s ASD diagnosis and communicating any social or communication difficulties to others in the event there are miscommunications that could lead to punitive consequences.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.046
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.046
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0020.004
Scholarly communication0.0030.003
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.051
GPT teacher head0.365
Teacher spread0.314 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations6
Published2018
Admission routes1
Has abstractyes

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