Disparities in cancer care: Perspectives from the front line
Bibliographic record
Abstract
OBJECTIVE: The purpose of this qualitative study was to investigate how frontline healthcare professionals witness and understand disparity in cancer care. METHOD: Six healthcare providers from a range of care settings, none with < 15 years of frontline experience, engaged with researchers in an iterative process of identifying and reflecting on equity and disparity in cancer care. This knowledge exchange began with formal interviews. Thematic analysis of the interviews form the basis of this article. RESULTS: Participants drew attention to health systems issues, the meaning and experience of discontinuities in care for patients at personal and community levels, and the significance of social supports. Other concerns raised by participants were typical of the literature on healthcare disparities. SIGNIFICANCE OF RESULTS: Providers at the front lines of care offer a rich source of insight into the operation of disparities, pointing to mechanisms rarely identified in traditional quantitative studies. They are also well positioned to advocate for more equitable care at the local level.
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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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.010 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| 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".