Risky Bodies: Implications of Risk and Risking in the Therapy Room
Bibliographic record
Abstract
Abstract Suicide risk assessment is seen as an integral component of psychotherapy practice; however, there is much debate surrounding the validity and efficacy of making such assessments. Specifically, the discourse of risk, including “risking” or “categorizing” individuals, has the potential to negatively impact the people whom psychologists/clinicians aim to serve. This dissertation aims to critically interrogate the notion of “risking” in suicide risk assessment to gain a better understanding of what works and what is harmful in suicide risk assessment procedures. Specifically, I interrogated the framing of “at risk” for 2SLGBTQ+ peoples, who are often perceived with this lens. Data from qualitative interviews and suicide risk assessment training materials was examined using a three-study model. The data was analyzed through reflexive thematic analysis and principles from critical discourse analysis, methodologically informed by social constructionism and drawing upon suicidism as a key conceptual consideration. This program of research expands theorizations surrounding the implications of suicide risk assessment practices and the ways that their nuances inform psychotherapeutic care. Keywords: suicide risk assessment, at risk populations, risk, risking, psychotherapy, 2SLGBTQ+ mental health
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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 | 0.018 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.017 | 0.051 |
| Scholarly communication | 0.016 | 0.012 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".