Not On Our Backs: Supporting Counsellors in Navigating the Ethics of Multiple Relationships Within Queer, Two Spirit, and/or Trans Communities
Bibliographic record
Abstract
Professional ethical guidelines commonly advise counsellors to avoid dual relationships wherever possible but generally have not provided guidance for situations where this is not feasible. This leaves queer, Two Spirit, and/or trans counsellors open to negative judgements, possible accusations of unprofessionalism, and practices of self-surveillance that limit their ability to live, work, and actively participate in the communities they serve. We argue that prohibiting dual relationships will neither end client exploitation nor account for the benefits that properly managed dual relationships can offer. The term multiple relationships may better reflect the complexity of relationships in queer, Two Spirit, and/or trans communities and acknowledges that they contain the potential of both harms and benefits for clients. We advocate for a richer engagement with ethics as a living entity that requires that we respond collectively as helping professions to ensure the care of marginalized communities without putting the burden of care on the backs of community members. We propose guidelines that call for the inclusion of all parties (counsellors, clients, and supervisors), transparency, full disclosure, and development of a plan and rationale for counsellors’ responsibilities in all encounters with clients both within and outside the clinical setting.
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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 | 0.051 | 0.083 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.033 | 0.027 |
| Scholarly communication | 0.019 | 0.018 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.011 | 0.019 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".