Client emotional productivity—optimal client in-session emotional processing in experiential therapy
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
OBJECTIVE: The goal of this investigation was to examine the predictive validity of Client Emotional Productivity (CEP), an operationalization of optimal client in-session emotional processing, possessing seven features: Attending, symbolization, congruence, acceptance, regulation, agency and differentiation. METHOD: CEP was related to improvement in depressive and general symptoms, in 74 clients (66% female, 34% male) who received experiential therapy of depression and this was compared to the relationship between client high expressed emotional (CHEEA) arousal and the working alliance (WAI) and outcome. RESULTS: Hierarchical regression analyses revealed that working phase CEP predicted significant reduction of depressive and general symptoms over and above that predicted by beginning phase CEP, the working alliance and working phase CHEEA. Working phase CEP emerged as the sole, independent predictor of outcome for both depressive and general symptoms. CONCLUSION: Productive emotional processing, thus, mediates the relationship between the alliance and outcome and seems to go beyond mere activation and expression of emotional experience. It rather seems to involve an increase in the ability to process activated primary emotion in a productive manner specified by CEP.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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 it