Awkward Choreographies from Cancer's Margins: Incommensurabilities of Biographical and Biomedical Knowledge in Sexual and/or Gender Minority Cancer Patients’ Treatment
Bibliographic record
Abstract
Canadian and American population-based research concerning sexual and/or gender minority populations provides evidence of persistent breast and gynecologic cancer-related health disparities and knowledge divides. The Cancer's Margins research investigates the complex intersections of sexual and/or gender marginality and incommensurabilities and improvisation in engagements with biographical and biomedical cancer knowledge. The study examines how sexuality and gender are intersectionally constitutive of complex biopolitical mappings of cancer health knowledge that shape knowledge access and its mobilization in health and treatment decision-making. Interviews were conducted with a diverse group (n=81) of sexual and/or gender minority breast or gynecologic cancer patients. The LGBQ//T2 cancer patient narratives we have analyzed document in fine grain detail how it is that sexual and/or gender minority cancer patients punctuate the otherwise lockstep assemblage of their cancer treatment decision-making with a persistent engagement in creative attempts to resist, thwart and otherwise manage the possibility of discrimination and likewise, the probability of institutional erasure in care settings. Our findings illustrate the demands that cancer places on LGBQ//T2 patients to choreograph access to, and mobilization of knowledge and care, across significantly distinct and sometimes incommensurable systems of knowledge.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.015 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".