Fat politics as a constituent of intersecting intimacies
Bibliographic record
Abstract
In this paper we explore the ways in which fat politics shapes (our) fat-thin intimacies as friends, colleagues and occasional lovers. We are queer writers who are actively engaged in fat politics; one of us is fat and the other is thin. We are both poets, scholars, and performers, privileged by whiteness, and contingently read as non-disabled. This paper takes the form of alternating reflections where we explore the nuances of our thoughts and feelings about friendship, romantic involvement, and engagement in learning communities. Specifically, we surface the ways that the various realms of our relationship are co-constituted by fatness, gender, and trauma histories. While we have both had fat and thin lovers before, Kimberly is the first fat, fat- affirming lover Lucy had, and Lucy is the first thin lover Kimberly had who was pre-educated and pre-experienced regarding fat stigma, fat shame, and social bias. We investigate what this shared political grounding made possible through the trust and vulnerability thus enabled. We also consider the erotic as an influence on scholarship which leads to praxis.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.017 | 0.065 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.001 | 0.021 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".