The Imperatives of Health and Weight in Primary Care Clinics: Current and Envisioned Practices
Bibliographic record
Abstract
Biopower imperatives about body weight, eating, and exercise are embedded in primary care practice. The dominant discourses about body weight frame the body as notably malleable, a direct reflection of eating and exercise behaviours, to the exclusion of other influences. In this dissertation, I aim to open dialogue on the question of how to care well for patients in a time when talking about weight, eating, and exercise is both expected and potentially stigmatizing and/or contributing to health disparities. I observed primary care appointments in three Alberta clinics, and a Canadian Obesity Network 5As of Obesity Management™ continuing professional development workshop. I interviewed the observed primary care clinicians, and key informants in the Canadian Obesity Network. Using analytic insights from discourse analysis, actor-network theory, and visual studies, I analysed both clinical practice and the workshop through the theoretical lenses of governmentality and Mol's logics of choice and care. In the clinic, weight-related talk elicited face-saving and confessional talk from most patients (that is, across body sizes), an indication of the strength of dominant discourses that assume malleability of bodies and behaviours, interpret fatness as failure, and reinforce individual responsibility for health. Clinicians’ responses to patients’ face-saving talk, and the ways in which clinicians used epidemiological knowledge to guide action varied. In the continuing professional development workshop, the Network’s vision moved obesity management closer to the logic of care, in part translating some obesities into a chronic disease frame through the folding in of a physiological theory to re-interpret epidemiological studies and clinical trials. This dissertation adds to conversations about anti-fat stigma and discrimination in health care, making visible some modes by which patients, clinicians, and knowledge brokers use and/or attempt to disrupt individualistic, blame-oriented discourses about fatness. The dissertation foregrounds a range of potential mediators that may influence translation of less-stigmatizing clinical practices into primary care clinics.
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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 | 0.041 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.024 | 0.045 |
| Scholarly communication | 0.020 | 0.011 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.006 | 0.008 |
| 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".