Corrective Experiences of Psychotherapists in Training
Bibliographic record
Abstract
Although the concept of corrective experiences (CEs) is usually linked to the process of change in psychotherapy patients, we investigated them in the professional development of therapists-in-training. Inasmuch as psychotherapy is a relational process, it is important to look closely at how therapists reach the position of a competent partner in corrective experiencing. In this study, we interviewed 10 therapists-in-training undergoing their own training therapy. Responses to these semistructured interviews were analyzed using a computer-assisted grounded theory method. The 499 first-level categories were grouped into 5 main themes: therapist characteristics, therapist technical interventions, therapist relational interventions, relationship experience, and outcome experience. Two core categories representing corrective experiencing were (a) unexpected unconditional support from and trust in their own therapist and (b) unexpected confrontation and limitation with their therapist as well as awareness of self-other boundaries. Results are discussed in the broader context of the CE literature, relational theory, and relational practice.
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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 | 0.005 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 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".