An Introduction to Using Microanalysis to Observe Co-construction in Psychotherapy
Bibliographic record
Abstract
In psychotherapy, co-construction refers to the proposal that the therapist and the client(s), in their dialogue, collaboratively create what emerges in their session. We trace the development of co-construction from its origins in postmodernism and point out that, unfortunately, it has remained more theoretical than practical or observable. The primary thesis of this article is that the microanalysis of video-recorded therapy sessions can render observable the details of how psychotherapists contribute to co-construction in any therapy session. Moreover, there is basic research on the microanalysis of face-to-face dialogue that applies directly to the understanding of co-construction in therapeutic dialogues. We demonstrate these proposals with an overview of the recent and growing body of empirical research on microanalysis of psychotherapy sessions. A detailed example from a therapy session illustrates four key aspects of co-construction: grounding between therapist and client(s), therapist's questions, therapist's formulations, and therapist's lexical choices.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.005 | 0.026 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".