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Record W1984748384 · doi:10.1080/10538712.2014.888123

Social Relationships in Sexually Abused Children: Self-Reports and Teachers’ Evaluation

2014· article· en· W1984748384 on OpenAlexafffund
Claudia Blanchard-Dallaire, Martine Hébert

Bibliographic record

VenueJournal of Child Sexual Abuse · 2014
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsUniversité du Québec à Montréal
FundersCanadian Institutes of Health Research
KeywordsLonelinessPsychologyFeelingSexual abuseChild sexual abuseClinical psychologyChild abusePoison controlVictimologyInterpersonal communicationInterpersonal relationshipSuicide preventionDevelopmental psychologySocial psychologyMedicineMedical emergency

Abstract

fetched live from OpenAlex

This study aimed to explore the social relationships of child victims of sexual abuse using both self-reports and teachers' ratings. Participants were 93 child victims of sexual abuse and a comparison group of 75 nonvictims. Teachers' assessments revealed that sexually abused children displayed greater social skill problems compared to same-age, nonabused peers and were more likely to display social difficulties nearing clinical levels. Analyses indicated that sexually abused children presented lower levels of interpersonal trust in people surrounding them yet a marginally higher level of trust in peers compared to nonabused children. Sense of loneliness and feeling different from peers did not differ between groups.

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)0.002
metaresearch head score (Gemma)0.008
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.313
Teacher spread0.281 · 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

Citations37
Published2014
Admission routes2
Has abstractyes

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