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Record W2123718266 · doi:10.1177/1079063213486835

Women Who Sexually Offend Display Three Main Offense Styles

2013· article· en· W2123718266 on OpenAlexaff
Theresa A. Gannon, Greg Waugh, Kelly Taylor, Kelly Blanchette, Alisha O’Connor, Emily Blake, Caoilte Ó Ciardha

Bibliographic record

VenueSexual Abuse · 2013
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsShared Services Canada
Fundersnot available
KeywordsPsychology

Abstract

fetched live from OpenAlex

This study examined a theory constructed to describe the offense process of women who sexually offend-the Descriptive Model of Female Sexual Offending (DMFSO). In particular, this report sets out to establish whether the original three pathways (or offending styles) identified within United Kingdom convicted female sexual offenders and described within the DMFSO (i.e., Explicit-Approach, Directed-Avoidant, Implicit-Disorganized) were applicable to a small sample (N = 36) of North American women convicted of sexual offending. Two independent raters examined the offense narratives of the sample and-using the DMFSO-coded each script according to whether it fitted one of the three original pathways. Results suggested that the three existing pathways of the DMFSO represented a reasonable description of offense pathways for a sample of North American women convicted of sexual offending. No new pathways were identified. A new "Offense Pathway Checklist" devised to aid raters' decision making is described and future research and treatment implications explored.

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)0.000
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.273
Teacher spread0.250 · 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

Citations62
Published2013
Admission routes1
Has abstractyes

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