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Record W2280871263 · doi:10.7870/cjcmh-2013-020

Les mauvais traitements psychologiques subis par les adolescents et adolescentes … des mots qui frappent!

2013· article· en· W2280871263 on OpenAlexaffvenue
Cynthia Bêty, Francine Lavoie, Danielle Nadeau

Bibliographic record

VenueCanadian Journal of Community Mental Health · 2013
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsUniversité LavalCentre Jeunesse de QuebecCentre hospitalier universitaire de Québec
Fundersnot available
KeywordsAttributionPsychologyPerceptionPoison controlSuicide preventionPopulationInjury preventionOccupational safety and healthClinical psychologyMedicineSocial psychologyMedical emergency

Abstract

fetched live from OpenAlex

This qualitative study investigated perceptions of Psychological Maltreatment (PM) with 19 adolescent victims referred to a child welfare agency. The research objectives were: (a) to explore youths’ causal attributions of PM, their perceived control of the PM situation, and their perceptions of the abuser; and (b) to document whether these perceptions differ as a function of the nature of the relationship between the youth and his or her abuser. Thirty-six critical incidents were investigated through semi-structured interviews with 19 participants. Interview transcripts were subjected to content analysis. Results highlight the subjective suffering of PM victims in this population and the difference in perceptions of this kind of violence according to whether intrafamilial or extrafamilial PM is involved.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.017
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.003
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.002
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 head0.078
GPT teacher head0.367
Teacher spread0.289 · 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 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

Citations0
Published2013
Admission routes2
Has abstractyes

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