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Record W2144643479 · doi:10.1177/1524838006297729

Vicarious Traumatization

2007· review· en· W2144643479 on OpenAlexaff
Heather M. Moulden, Philip Firestone

Bibliographic record

VenueTrauma Violence & Abuse · 2007
Typereview
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPsychologyPsychotherapistCoping (psychology)Clinical psychology

Abstract

fetched live from OpenAlex

This article reviews the descriptive and empirical literature examining vicarious traumatization in therapists treating sexual offenders. Vicarious traumatization in sexual offender therapists is described, including an examination of the relationships between vicarious traumatization and client, therapist, and setting and therapy characteristics. Special attention is given to those unique factors that contribute to the development of vicarious traumatization in this group, as well as consideration of why therapists treating offenders or victims may differ in their experience and development of vicarious traumatization. Evidence from the research reviewed suggests that sexual offender therapists do experience symptoms of vicarious traumatization. Factors most strongly associated with the development of vicarious traumatization in sexual offender therapists include professional experience, treatment setting, and coping strategies employed by the therapists. Implications and recommendations for professionals and policymakers are discussed.

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)0.006
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: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0010.003
Scholarly communication0.0030.004
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.211
GPT teacher head0.486
Teacher spread0.275 · 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
GenreReview

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

Citations120
Published2007
Admission routes1
Has abstractyes

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