Bibliographic record
Abstract
Canada’s human papillomavirus vaccination program should be halted immediately until its safety can be established, a researcher who has studied patient experiences of the vaccine under a government grant has said. Genevieve Rail, a professor of critical studies of health at Montreal’s Concordia University, has a $C273 359 (£135 000; €185 000; $208 000) grant from the Canadian Institutes of Health Research for research entitled “HPV vaccination discourses, spaces and biopedagogies: Affects and effects on youth’s bodies and subjectivities.” She reports having gathered 170 families whose recounted stories indicate a heavy burden of vaccine injury. Writing in the Quebec daily newspaper Le Devoir , Rail and her coauthor Abby Lippman, a former professor in McGill University’s department of epidemiology, biostatistics, and occupational health, argued that the vaccine was given to schoolgirls without obtaining proper informed consent.1 They said that it had caused serious adverse events around the world, that Canada’s system of reporting was inadequate to detect problems, that it was a misplaced priority because cervical cancer was not a leading cause of death, that its efficacy was not proven, that it may even exacerbate precancerous lesions, and that it was fraudulently marketed and too hastily approved. “Across the world,” the authors wrote, “young vaccinated girls are the protagonists in a drama of which only the pharmaceutical companies know the …
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 | 0.023 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.047 | 0.023 |
| Scholarly communication | 0.016 | 0.009 |
| Open science | 0.006 | 0.009 |
| Research integrity | 0.036 | 0.037 |
| Insufficient payload (model declined to judge) | 0.033 | 0.005 |
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".