Bibliographic record
Abstract
Sam Hamburg's (2018) case studies of the use of metaphoric tasks in psychotherapy take us into the storied course of therapy with "Margie" and with "Amy." In the nuances of Hamburg's accounts of these two sometimes similar, often different case studies, we see how metaphoric tasks can be conceived, implemented, and understood, and how the sensory-evoking, relationship-enhancing potential of metaphor can be enacted. We also see at work a deeply committed, thoughtful, and skilled practitioner-researcher who is, at once, cautious in his claims about the relation between metaphor use and therapy outcome, confident in what he knows about the practice of psychotherapy, and wise in his integration of the two.
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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 | 0.013 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.013 | 0.076 |
| Scholarly communication | 0.030 | 0.044 |
| Open science | 0.002 | 0.025 |
| Research integrity | 0.010 | 0.016 |
| Insufficient payload (model declined to judge) | 0.020 | 0.006 |
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".