Multiculturalism and solution-focused psychotherapy: an exploration of the nonexpert role
Bibliographic record
Abstract
Orientalism is described as the ‘grandest of all narratives’ (Edward Said, 1978 Said, E. 1978. Orientalism, Routledge: London. [Google Scholar]) Zai sheng huo zhong, mei li de xiao, you ya de chou (In life, beautifully smile, gracefully worry) (From Van Leeuwen, 2005 Van Leeuwen, T. 2005. Introducing social semiotics, London: Routledge. [Google Scholar], p. 153) The role of the solution-focused psychotherapist (SFP) is less about confirming the rights of the client as an individual and more about amplifying their preferred social performance. The client, the therapist and the drama of therapy represent the object of this performance in which cultural meaning is simply amplified. The identity of the client is framed within multicultural narratives and discourse with which the psychotherapist grapples and strives to maintain a type of neutrality and equality, a relationship of nonexpertness. It is the client who has the resources and who is expert in their own lives. Yet, the drama conflict is one in which the client expects certain answers, reassurances and direction. This article is an exploration of issues related to counselling technologies, language and culture on the solution-focused notion of nonexpert practice.
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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 | 0.011 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.011 | 0.045 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.002 | 0.004 |
| 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".