Cancer among Indigenous Communities: Disparities & Challenges
Bibliographic record
Abstract
Given the history of racism and systemic oppression of Indigenous communities, examining and addressing health inequities in in Indigenous continues to be relevant and important. An increasing number of healthcare problems are emerging from Indigenous communities.1,2 Canadian First Nations women and men have lower life expectancies and increasing rates of chronic conditions, such as diabetes, cardiovascular diseases, heart disease, and obesity.1 Some evidence suggests that the burden of cancer is lower among Indigenous communities than the overall population.3 However, there is much data indicating that this rate in increasing and that members of Indigenous communities have increased mortality rates when compared to non-Indigenous groups for cancers of the cervix, breast, gallbladder, lip and oropharynx, liver, lung, prostate and stomach.4,5 This paper discusses cancer incidence, risk factors, screening, and detection of cancers among Indigenous communities. This is followed by a discussion of potential interventions that may reduce the burden-related morbidity and mortality of cancer on these communities. Indigenous communities continue to experience unique barriers to accessing appropriate cancer care and preventive services and steps to minimize health inequalities should be taken.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".