Social Justice and the Word: Keeping Diversity Alive in Therapeutic Conversations
Bibliographic record
Abstract
The question of social justice is gaining attention in examinations of the scope of counselling and psychotherapy practice. There is a growing recognition that persons seeking therapeutic services are not merely manifesting individual personalities, but dealing with social inequities that help to illuminate the problems they describe. An outgrowth of this insight is the call to expand the therapist’s role into advocacy by extending the practice of counselling beyond the consulting room. Although celebrating these developments, this article makes a case for how social justice and injustice not only unfold in the broader social arena; they also play out, utterance by utterance, in therapeutic conversations. After demonstrating how therapeutic conversations can be understood as sites of identity construction, the article offers a range of questions for aiding practitioners in “doing justice” in their exchanges 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 | 0.021 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.053 | 0.139 |
| Scholarly communication | 0.030 | 0.037 |
| Open science | 0.004 | 0.032 |
| Research integrity | 0.010 | 0.013 |
| 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".