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Record W7096768644

Exploring taboos: Comparing male and female perpetrated child sexual abuse

2009· article· en· W7096768644 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsSexual abuseChild sexual abuseSocioeconomic statusChild abusePoison controlDomestic violenceIncidence (geometry)Suicide prevention
DOInot available

Abstract

fetched live from OpenAlex

The objective of this article is to compare male- and female-perpetrated sexual abuse in terms of victim and abuser characteristics, type of abuse, family structure, and worker information. Bivariate tests of significance were performed on the 1998 Canadian Incidence Study of Reported Child Abuse and Neglect, which included 308 male and 37 female abusers. Results show a prevalence rate of 10.7 % for female-perpetrated sexual abuse. Girls were more likely to be victimized for both male- and female-perpetrated sexual violence and females tended to abuse younger children. The majority of children came from families with lower socioeconomic status although one in five victims of female-perpetrated sexual abuse came from middle-class homes. Referrals to child welfare agencies were more likely to be made by nonprofessionals when females abused.

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)0.013
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 score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
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 head0.114
GPT teacher head0.301
Teacher spread0.187 · 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
Published2009
Admission routes1
Has abstractyes

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