A High-Risk Body for Whom? On Fat, Risk, Recognition and Reclamation in Restorying Reproductive Care through Digital Storytelling
Bibliographic record
Abstract
This paper explores issues of weight stigma in fertility, reproduction, pregnancy and parenting through a fat reproductive justice lens. We engage with multimedia/digital stories co-written and co-produced with participants involved in Reproducing Stigma: Obesity and Women’s Experiences of Reproductive Care. This mixed methods research project which took place between 2015-2018 used interview and video-making methods with women-identified and trans people, as well as interviews with healthcare providers and policymakers to investigate perceptions and operations of weight and other stigma in fertility and pregnancy care. We consider the ways in which reproductive risk is typically storied in healthcare and culture, and analyse multimedia/digital stories made by participant-video-makers which story reproductive wellbeing differently. We examine three major themes—on risk, on recognition of weight and other stigma, and on reclamation of bodies—that emerged as critical to these storytellers as they navigated fatphobia in reproductive care. We argue that just as healthcare practitioners strive to practice evidence-based care we must also put into practice storied care—to believe, respect and honour fat people’s stories of their bodies and lives as fundamental to achieving equity and justice in reproductive healthcare.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".