Access to Colorectal Cancer Screening in Canada: Does Immigrant Status Matter
Bibliographic record
Abstract
Background: In 2010, immigrants comprised 20% of the Canadian population. Canada has one of the highest incidence and mortality rates of colorectal cancer (CRC) in the world. This study seeks to explore factors that are associated with CRC screening and to determine whether immigrants are less likely to be screened for CRC compared to non-immigrants. Methods: Data were obtained from Statistics Canada Canadian Community Health Survey, 2008. The Behavioral Model of Health Services Use was used as a theoretical framework. Chi-square statistics and multiple logistic regression models were employed. Results: Recent immigrants were less likely to be screened by endoscopy within 5 years (OR: 0.47; 95% CI: 0.29 – 0.77), endoscopy within 10 years (OR: 0.38; 95% CI: 0.24 - 0.60) and be up-to-date with screening (OR: 0.58; 95% CI: 0.37 - 0.91) compared to non-immigrants. Conclusions: A formal screening program and patient navigators may address disparities among recent and non-immigrants.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".