Fat Pedagogy in Action: Size Inclusivity in Public Library Health and Wellness Programming
Bibliographic record
Abstract
Informed by the developing field of fat studies and inclusive of fat voices, this study explores whether sizeism associated with popular health and wellness culture appears in public library health programs. We conducted thematic content analyses of health and wellness–related public library program descriptions in the United States and Canada as well as library conference materials and resources used by library workers to develop health-related programs and resources to provide a broad picture of the narrative around health in libraries. While we found public libraries’ health programming to not be explicitly fat-phobic, there is still room for improvement. We employ fat pedagogy ( Cameron & Russell, 2016 ) to offer recommendations to address sizeism in a way that advances the cause of fat liberation and supports library workers’ and graduate library and information science programs’ existing commitments to respect and inclusivity.
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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 | 0.013 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.022 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.018 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".