Review of Treating chronic depression with disciplined personal involvement: Cognitive behavioral analysis system of psychotherapy (CBASP).
Bibliographic record
Abstract
Reviews the book, Treating chronic depression with disciplined personal involvement: Cognitive behavioral analysis system of psychotherapy (CBASP) by James P. McCullough Jr. (see record 2006-11486-000). The premise of this book is that therapeutic neutrality does not apply to the psychotherapy of chronically depressed individuals, and that disciplined personal involvement is an efficacious and perhaps necessary component of their treatment. Cognitive behavioral analysis system of psychotherapy (CBASP) is a learning model, in which the therapist focuses on teaching patients to recognize the consequences of their behavior. McCullough addresses practical and theoretical objections to this therapeutic approach, which include fears of overinvolvement, and inappropriate behavior, and clinical risks of flooding patients with excessively personal information and content. Ultimately, most readers will finish reading this volume with many open questions, some specific to McCullough's approach, others related to the challenging condition of chronic depression itself. (PsycINFO Database Record (c) 2010 APA, all rights reserved).
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".