Silent No More Coming Out About Lesbians and Cancer
Bibliographic record
Abstract
Des recherches qualitatives lues en public ont donnilieu a un forum a j n de digager les dzffirents niveaux des histoires recueillies auprks des participantes d i n e recherche. Cet article est le reflet des histoires de 26lesbiennes de /'Ontario qui ont iti interuiewies au sujet de leur cancer du sein, des traitements, des soins reps, du support social et de leur perception etsentimentau sujetde leur identiti, de leur corps, de leur sexualiti et de leurs amitiks.-In memory ofPauline Bradbrook, a found-ing leader, a courageous advocate, an inspiring colleague, a loving piend Developing effective dissemination strategies for commu-nity-based research studies is often a multi-step process wherein the project team decides: 1) who one wants to reach with the information collected; 2) how best to reach these "target " audiences; and 3) what one wants to convey.
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 | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.020 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.012 | 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".