Power and dialogue: A review of discursive research
Bibliographic record
Abstract
Collaborative-dialogic approaches to family therapy advise therapists to take a position of client-as-expert and promote an equality of multiple perspectives. This has led to debates about how to conceptualize power in dialogical therapies with scholars theorizing and researching power as social and negotiated through interaction. We aimed to understand power in dialogical therapy through reviewing discursive research on therapeutic conversations. We performed a systematic search of bibliographical databases PsycINFO, PubMed, and CINAHL. We reviewed the findings from 18 studies utilizing discursive analyses of collaborative-dialogical therapy sessions and examined their findings in relation to power within interactions. We found a strong focus on the practices of the therapist rather than on those of the client. The therapist was presented as a catalyst of dialogue using minimal and active responses to promote dialogical conversations. Therapists also utilized power in response to broader institutional and social demands that may not be consistent with some interpretations of dialogical therapy. We consider practice implications where the exercise of power to direct a session facilitates dialogical interactions.
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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 | 0.022 | 0.051 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.030 | 0.028 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".