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Record W2105227332 · doi:10.7202/017292ar

Victimes d’actes criminels : une intervention professionnelle

2005· article· en· W2105227332 on OpenAlexaffvenue
Frema Engel

Bibliographic record

VenueCriminologie · 2005
Typearticle
Languageen
FieldHealth Professions
TopicHealth, Medicine and Society
Canadian institutionsMinistère de l’Emploi et de la Solidarité Sociale (Québec)
Fundersnot available
KeywordsIntervention (counseling)PsychologyMental healthCriminologyPsychiatryNursingMedicine

Abstract

fetched live from OpenAlex

Victims of crime suffer tremendous psychological damage as a result of the trauma that they experience. The effects can be totally debilitating and can destroy their lives. The author discusses the reactions, symptoms of acute stress and stages of recovery of crime victims. She also discusses post-traumatic stress syndrome (PTSD), and the kind of help victims need to recover from their injuries. Finally, she suggests how mental health professionals in particular and society in general could better respond to crime victims.

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)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0070.005
Scholarly communication0.0030.003
Open science0.0010.003
Research integrity0.0070.005
Insufficient payload (model declined to judge)0.0040.001

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 head0.424
GPT teacher head0.517
Teacher spread0.093 · 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 designNot applicable
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

Citations2
Published2005
Admission routes2
Has abstractyes

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