Narrative measures in psychotherapy research: Introducing the special section
Bibliographic record
Abstract
[Excerpt] The aim of this special section is to present a review of recent advances in the assessment of changes in client narratives. An emerging trend in the psychotherapy research field suggests that narrative-based meaning reconstruction is an important foundation for the articulation of a new, more adaptive view of self (Angus & Kagan, 2013) in psychotherapy. Additionally, a range of research-informed treatment models, including psychodynamic (Luborsky, 1998), humanistic (Angus, Watson, Elliott, Schneider, & Timulak, 2015) and systemic therapy approaches (Dallos & Vetere, 2009), emphasize that client changeinpsychotherapyisfacilitatedthroughpersonal story disclosure, emotional engagement and reflection for new meaning construction and self-narrative reorganization. In fact, recent research from Angus et al. (inpress)andGonçalvesetal.(thisissue),usingdifferent methods and clinical samples, have independently established that successful psychotherapy involves client self-narrative transformation processes evidenced in late phase therapy sessions. (...)
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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 teacher head, 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".