Indigenous communities in Colombia: A cultural and holistic view of cancer management
Bibliographic record
Abstract
Cancer is one of the most burdening global health challenges. Indigenous communities are at high risk for worse healthcare outcomes because of inequalities in the incidence, prevalence, and mortality of oncological diseases, that arise from socioeconomic, racial, cultural, religious beliefs, and ethnic factors. Their perception about themselves is closely related to what affects their territory, making them possess a profound rooted feeling with their surroundings, and intense spiritual believes. Consequently, the disease process is linked to physical and emotional imbalances and alterations in their territory. Researchers from the United States, Canada, New Zealand, and Australia have worked diligently to learn about barriers to cancer management among these populations. Unfortunately, robust cancer data is lacking for most of the world's Indigenous, leading to obstacles in information systems and consequently, inequities in healthcare with the perpetuation of the problem. Therefore, a better understanding of cancer as a global health problem is required. Our study aims to propose a holistic and culturally adapted framework to improve cancer health services and outcomes among Indigenous peoples in Colombia.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".