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Record W1544650217 · doi:10.1177/104973150001000301

What Children Learn from Sexual Abuse Prevention Programs: Difficult Concepts and Developmental Issues

2000· article· en· W1544650217 on OpenAlexaff
Leslie M. Tutty

Bibliographic record

VenueResearch on Social Work Practice · 2000
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSexual abuseIntervention (counseling)Child sexual abusePsychologyChild abuseClinical psychologyDevelopmental psychologySuicide preventionPoison controlMedicinePsychiatryMedical emergency

Abstract

fetched live from OpenAlex

Objective Social workers have long been concerned about whether child-directed school-based programs are effective in preventing sexual abuse. Knowing children's prior knowledge of abuse prevention concepts and what changes after intervention would be invaluable to program personnel. Method This secondary analysis involved 231 elementary school children who were randomly assigned (matched by age) to participate in the “Who Do You Tell” sexual abuse prevention program (n = 117) or in a wait-list control condition (n = 114). Chi-square analyses compared changes on each item of the Children's Knowledge of Abuse Questionnaire-Revised based on treatment versus control condition and developmental level (ages 5 to 7 compared to ages 8 to 13). Results Three items significantly improved for children in the program as compared to those in the control condition across ages. Conclusions The results suggest several changes in teaching prevention concepts.

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)0.006
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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.120
GPT teacher head0.474
Teacher spread0.354 · 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

Citations70
Published2000
Admission routes1
Has abstractyes

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