Narrative quality and disturbance pre‐ and post‐emotion‐focused therapy for child abuse trauma
Bibliographic record
Abstract
This study predicted that the quality of trauma narratives written before and following emotion-focused therapy for child abuse trauma would be positively associated with psychological disturbance before and following therapy. Narratives for 37 clients were coded for emotion words, temporal orientation, incoherence, and depth of experiencing. At pretreatment, negative emotion words and experiencing were correlated with abuse resolution, r(35) = -.36, and r(35) = -.34, respectively. At posttreatment, narrative incoherence was correlated with trauma symptoms, r(35) = .33, whereas present-future orientation and experiencing were correlated with abuse resolution, r(35) = -.37, and r(35) = -.31, respectively. Pretreatment incoherence was associated with posttreatment trauma symptoms, r(35) = .42, and pretreatment depth of experiencing was associated with posttreatment abuse resolution, r(35) = -.37. Results support narrative quality as an index of trauma disturbance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".