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Record W3081714115

Secondary traumatic stress in Canadian school counsellors: presence and prediction

2011· dissertation· en· W3081714115 on OpenAlexaboutno aff
Andrea D. Moore

Bibliographic record

VenueMspace (University of Manitoba) · 2011
Typedissertation
Languageen
FieldPsychology
TopicCounseling Practices and Supervision
Canadian institutionsnot available
Fundersnot available
KeywordsTraumatic stressStress (linguistics)PsychologyClinical psychologyMedicine
DOInot available

Abstract

fetched live from OpenAlex

A non-experimental survey design was used to study participant self-identified presence of secondary traumatic stress (STS) in Canadian school counsellors (N = 57) in relation to counsellors’ education and training, trauma-specific training, work experience, supervision, number of trauma clients and coping strategies. Counsellors were not necessarily protected from STS if they spent time using coping strategies, but were much less likely to be affected by STS if they engaged in supervision. Many school counsellors (59.6%) who participated in this research do engage in supervision, and those with trauma-specific training were less likely to have a peer-identified trauma disorder. Peer-identified trauma disorder played a large role in the results of this study. Participants identified as suffering from a trauma disorder were very likely to have a formal trauma diagnosis and were also likely to have higher traumatic stress scores. Implications for future research and education and training 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)0.008
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 score0.068
Threshold uncertainty score0.137

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.021
GPT teacher head0.244
Teacher spread0.223 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

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