A Knowledge Translation Event on Colorectal Cancer Screening in a First Nations Community.
Bibliographic record
Abstract
INTRODUCTION: Colorectal cancer (CRC) screening reduces incidence of and mortality from CRC. First Nations have higher rates of CRC incidence and mortality and lower rates of screening compared to non-First Nations. We aimed to increase awareness of the importance of CRC screening in the First Nations community of Kahnawake, Quebec, Canada. METHODS: We held a knowledge translation (KT) event in Kahnawake, a Mohawk community located 12 miles from Montréal, Québec. The event was advertised in the local community through posters, newspaper advertisements and radio announcements and on websites of the Canadian Institutes of Health Research, Canadian Cancer Society and Colorectal Cancer Association of Canada. Three presenters with expertise in research, public health nursing and gastroenterology spoke about various aspects of CRC screening. General topics included the biology of CRC, the benefits of CRC screening and different CRC screening tests, and research findings on ways to improve people's CRC screening experience. Topics of special interest included the increasing rates of CRC in Canadian Aboriginal people, the modifiable and non-modifiable risk factors for developing CRC, how to access CRC screening in the community, and how to use the new fecal immunochemical test.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.109 | 0.013 |
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".