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.
Bibliographic record
Abstract
In Emotion-Focused Therapy for Depression, Leslie S. Greenberg and Jeanne C. Watson, well-regarded scholars and leading figures in the field, provide a manual for the emotion-focused treatment (EFT) of depression. Their approach is supported by studies in which EFT for depression was compared with Cognitive-Behavioral Therapy, Client-Centered Therapy, and then both. The approach has been refined to apply specifically to the treatment of this pervasive and often intractable disorder. The authors discuss the nature of depression and its treatment, examine the role of emotion, present a schematic model of depression and an overview of the course of treatment, and suggest who might benefit. Written with a practical focus rather than the more academic theoretical style of previous books that established the theoretical grounds and scientific viability of working with emotion in psychotherapy, this book aims to introduce practitioners to the idea of using this approach to work with a depressed population. The book covers theory, case formulation, treatment, and research in a way that makes this complex form of therapy accessible to all readers. Particularly valuable are the case examples, which demonstrate the deliberate and skillful use of techniques to leverage emotional awareness and thus bring about change.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 it