Bibliographic record
Abstract
When the Call for Papers was drafted and sent out—to NGOs and activist alliances across Canada, and in the UK, Ireland, Australia and the US; and to historians and academics in the field of gay and lesbian studies; and to various individuals—I think that neither Cheryl nor I truly knew what to expect. We received some correspondence disputing the grouping of Lesbian, Gay, Bisexual and Transgendered Peoples as reaffirming the “medical” use and scientific degradation of queer peoples’ bodies and histories. The “disease” model of non-heterosexualities is still very much in many people’s consciousnesses, not least those who have been historically named as deviant, aberrant, unnatural, perverse or sick—which includes every lesbian, gay man, bisexual and transgendered person you can name or imagine. Given the history of attacks—both physical and discursive—upon the “truths” of our lives and the consequent neglect and marginalization we often still endure, this does not surprise me.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.011 | 0.008 |
| Insufficient payload (model declined to judge) | 0.130 | 0.041 |
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".