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Record W2664163986 · doi:10.1002/jcad.12142

Trauma Competency: An Active Ingredients Approach to Treating Posttraumatic Stress Disorder

2017· article· en· W2664163986 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Counseling & Development · 2017
Typearticle
Languageen
FieldPsychology
TopicPsychotherapy Techniques and Applications
Canadian institutionsToronto Rehabilitation Institute
Fundersnot available
KeywordsPsychoeducationCognitive restructuringPsychotherapistRelaxation (psychology)PsychologyPosttraumatic stressCognitionClinical psychologyMedicinePsychiatrySocial psychologyIntervention (counseling)

Abstract

fetched live from OpenAlex

Meta-analytic studies have extracted 4 common elements among effective posttraumatic stress disorder treatments: cognitive restructuring and psychoeducation, a deliberate and continually improving therapeutic relationship, relaxation and self-regulation, and exposure via narrative of traumatic experiences. The authors present a clinical treatment structure catalyzing these active ingredients into discrete therapeutic tasks that counselors can focus on to maximize treatment effectiveness. The 4 tasks represent an attempt to identify critical competencies and baseline standards for the field of trauma counseling.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.814
Threshold uncertainty score0.655

Codex and Gemma teacher scores by category

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

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 head0.040
GPT teacher head0.361
Teacher spread0.321 · 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