Dying to Learn: A Scoping Review of Breast and Cervical Cancer Studies Focusing on Black Canadian Women
Bibliographic record
Abstract
BACKGROUND: In Canada, data on race/ethnicity are not routinely collected. Black Canadian women may be under-screened for cervical/breast cancer and may be predisposed to worse outcomes, however data are difficult to find. OBJECTIVES: A scoping review was conducted to identify common themes and gaps in the literature regarding cervical/breast cancer prevention and management in Black Canadian women. METHODS: Medline, Embase, the Cochrane Library, CINAHL, PsycINFO, and Scopus databases (2003-2018) and grey literature were searched. Relevant studies were selected, data were charted, and themes were extracted. RESULTS: Twenty-three studies met inclusion criteria. Women from sub-Saharan Africa appear to have lower cervical and breast cancer screening rates; those of Caribbean/Latin American origin appear to have screening rates comparable to the general population; no studies reported prevalence or mortality rates for Black Canadian women. CONCLUSION: There is a paucity of health research on breast and cervical cancer specific to Black Canadian women.
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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 | 0.014 | 0.055 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.021 | 0.031 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".