Exploring corrective experiences in a successful case of short-term dynamic psychotherapy.
Bibliographic record
Abstract
The concept of corrective emotional experience, originally formulated by psychoanalysts Alexander and French (1946), has been redefined by contemporary researchers to be theoretically nonspecific, that is, as "coming to understand or experience an event or relationship in a different or unexpected way" (Castonguay & Hill, 2011). Using postsession questionnaires, videotapes, and posttermination interviews, we explored whether (and how) a corrective experience occurred in a successful case of short-term dynamic psychotherapy (STDP; Davanloo, 1980). A 35-year-old woman suffering severe panic attacks was seen for 31 sessions by an experienced STDP therapist. The questionnaires and interviews focused on (a) perceived intrapsychic and interpersonal changes, and (b) how these changes came about. At termination, the client reported complete symptom relief, greater self-acceptance, improved relationships, and more emotional flexibility. Her corrective experience was evident in the qualitative themes, which showed that she came to understand and affectively experience her relationships with both parents differently. Moreover, the themes reflected both STDP-specific (e.g., confrontation of defenses) and nonspecific (e.g., rapport, acceptance) mechanisms of change. Conversation analysis (Sacks, 1995) of what the client described as "the 'gentle shove' of questions that make me see what I have been trying to ignore since childhood" showed, on a microlinguistic level, how she overcame resistance to strong emotional experience and expression.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| 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".