Constructive conversations: Revisiting selected developments with clients and counsellors
Bibliographic record
Abstract
Abstract Aim: to examine client and counsellor experiences in using and responding to social constructionist (e.g. solution‐focused, narrative and collaborative approaches) questions and other conversational interventions. Method: retrospective comments were elicited from 32 clients and 12 counsellors (trained in social constructionist counselling approaches) in reviewing their videotaped use of (or response to) questions and interventions from the social constructionist approaches in single session lifestyle consultations. These comments were transcribed then analysed using the constant comparison method of grounded theory. Results: five common themes (but with different emphases for clients and counsellors) were identified: exploring and adopting the client's perspective; identifying alternative perspectives; identifying strengths, possibilities, and solutions; developing a shared understanding; struggling to talk in a different way. Conclusions: the findings will be useful to counsellors interested in improving their responsive use of questions and interventions in dialogues with clients.
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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 | 0.026 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.017 | 0.014 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.004 | 0.006 |
| 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".