The Experiences of Ethical Tensions When Using Harm Reduction with High-Risk Youth
Bibliographic record
Abstract
Little is known about the ethical experiences of psychologists who work with high-risk youth using a harm reduction approach. We used interpretative phenomenological analysis (IPA) to explicitly explore this phenomenon. In this small exploratory study three participants were interviewed to glean their experiences of ethical tension. Data analysis revealed three superordinate themes (questioning, acting, and holding) within which eight subthemes are subsumed (questioning beneficence, questions from others, self-care, social change, negotiation, consultation and supervision, acceptance, and sitting with tension). The results of this research suggest that context-specific ethical tensions may arise for psychologists who work with high-risk youth using a harm reduction approach, which in turn lead to and necessitate a tailored ethical response. The results also suggest that harm reduction promoters may benefit from increased dialogue with licencing and professional bodies to foster awareness and develop guidelines on promoting ethical practice when using a harm reduction approach with high-risk youth. Future research can profitably be directed towards an increased experiential understanding of some of the central themes of this research, such as “sitting with tension” and “holding.”
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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 | 0.019 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.022 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.001 | 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".