Client Attitudinal Stance and Therapist-Client Affiliation: A View from Grammar and Social Interaction
Bibliographic record
Abstract
Although it is widely acknowledged in psychotherapy research that the de-velopment and maintenance of positive relational bonds are central to the therapeutic process, the ways that therapists and clients become affiliated through discourse and interaction has not received very much attention. Taking up this concern from a conversation analytic perspective, this paper explores how therapists and clients negotiate affiliation around clients’ affective and evaluative talk or attitudinal stance. In order to illustrate the application of our method, we have chosen to analyze audio- and video-recordings of two clinically relevant interactional contexts in which client stance constructions frequently occur: (1) client narratives; (2) client disagreements with therapists. We show that therapist responses to client attitudinal stances play an important role not only in securing affiliation and positive relational bonds with clients, but also in moving the interaction in a therapeutically relevant direction.
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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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.004 | 0.041 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.002 |
| 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".