Afrocentric screening program for breast, colorectal, and cervical cancer among immigrant patients in Ontario
Bibliographic record
Abstract
PROBLEM ADDRESSED: Black and immigrant populations across Canada have lower screening rates than Canadian-born white populations, predisposing them to increased cancer morbidity and mortality. Effective interventions are required to increase cancer screening rates among these populations. OBJECTIVE OF PROGRAM: To improve breast, colorectal, and cervical cancer screening rates at TAIBU Community Health Centre, which has a mandate to provide primary health care services to the Black and immigrant community in the greater Toronto area. PROGRAM DESCRIPTION: An Afrocentric quality improvement program was developed and implemented, consisting of provider audits, cancer screening education programs, a patient call-back program, and a mammography promotion day. CONCLUSION: TAIBU Community Health Centre's continuous quality improvement approach was successful in engaging health care providers and patients to increase cancer screening participation sustainably in a racially and socioeconomically diverse setting. Rates of breast, colorectal, and cervical cancer screening offered to eligible patients increased from 17% to 72%, 18% to 67%, and 59% to 70%, respectively, between 2011 and 2018.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".