‘I Just Need to Get to Know You’: A Foucauldian Genealogy of Health Care Assessments of Trans and Gender Diverse Youth
Bibliographic record
Abstract
Despite the importance of transition related health care (TRHC) for many trans and gender diverse (trans) youth, there are many barriers to accessing this care, including assessment protocols that limit youth’s autonomy. This research seeks to interrogate how and why current assessment practices in pediatric TRHC in Ontario have come to be. Drawing on the theories of (trans)normativity and governmentality, the project applied a Foucauldian discourse analysis to analyze interviews with five clinicians currently practicing in TRHC in Ontario. Analysis identified six sources which influenced clinicians’ assessment practices: clinical guidelines, more experienced clinicians, other experience in pediatric care, evolving research and evidence, perspectives of youth and families, and external legal and social pressures. Additionally, analysis interrogated the evolution of mental health assessments from the realm of psychology and psychiatry to an embedded part of clinical care; the oft-repeated intention of clinicians to “get to know” youth; and the conditional decision-making authority, granted to some, but not all, trans youth. Findings discuss how these discourses obscure the ways in which power is enacted within the clinic. Finally, this project explores the implications of these findings for provider training, clinical practice, and theory. This research is put forward in the hope that, in the future, all trans and gender diverse children and youth will have access to the affirming TRHC that they need and deserve.
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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 | 0.012 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.024 | 0.048 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 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".