MétaCan
Menu
Back to cohort
Record W4393201415 · doi:10.1080/13552600.2024.2331146

Historical child sexual abuse cases reported to the police by Indigenous adults in a northern Canadian territory: an exploration of factors affecting the likelihood of charges and convictions

2024· article· en· W4393201415 on OpenAlexaboutno aff
Kate Chenier, Andrea Shawyer, Andy Williams, Rebecca Milne

Bibliographic record

VenueJournal of Sexual Aggression · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicMilitary, Security, and Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousHuman factors and ergonomicsPoison controlSuicide preventionOccupational safety and healthInjury preventionPsychologySexual abuseCriminologyChild abuseChild sexual abuseMedical emergencyPsychiatryMedicinePolitical scienceLaw

Abstract

fetched live from OpenAlex

The current research examined historical child sexual abuse files from a northern Canadian police force, looking at factors pertaining to the offence, the complainant and the suspect, in an area with a large Indigenous population. The dataset analysed represented all reported cases (N = 229) of historical child sexual abuse by Indigenous complainants in the database of the participating force from 2005 to 2019. Analysis of all cases showed charges were more likely in cases with multiple complainants, female complainants and complainants 11–14 years old at the time of the abuse. For cases where charges were laid (n = 135), convictions were slightly more likely in cases with less serious offences. For trial cases (n = 75), multiple complainants, the relationship of suspect to complainant, age of suspect and age difference between complainant and suspect were significantly associated with trial outcome. Ethnicity of suspects showed no relationship to charges or convictions.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.279
Threshold uncertainty score0.430

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.045
GPT teacher head0.323
Teacher spread0.278 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Sexual AggressionSame topicMilitary, Security, and Education StudiesFrench-language works237,207