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Record W4283578239 · doi:10.5281/zenodo.6726600

Gender Differences in Aggressive Behaviours Among Individuals with Intellectual Disability: The Moderating Role of Vulnerability Factors

2022· article· en· W4283578239 on OpenAlexaff
Mélissa Clark, Diane Morin, Anne G. Crocker

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsInstitut national de psychiatrie légale Philippe-PinelUniversité du Québec à Montréal
Fundersnot available
KeywordsVulnerability (computing)PsychologyIntellectual disabilityDevelopmental psychologySocial psychologyPsychiatryComputer security

Abstract

fetched live from OpenAlex

The factors contributing to aggressive behaviours among individuals with intellectual disability (ID) are not fully understood. The goal of the present study was to examine whether vulnerability factors such as ID severity, speech, or motor impairments moderated gender differences in aggressive behaviours. Adults (n=296) with ID were recruited, and data on vulnerability factors and aggressive behaviours were collected through file reviews and interviews. Moderation analyses indicated that men were more likely to exhibit physical aggression than women, particularly those with a mild level of ID. Analyses also indicated that women were more likely to exhibit physical aggression than men, particularly those with speech impairment. Our findings suggest that gender-dependent vulnerability factors might contribute to aggressive behaviours among individuals with ID.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.073
GPT teacher head0.296
Teacher spread0.223 · 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 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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)→Same topicFamily and Disability Support Research→French-language works237,207→