Health and healthcare equity within the Canadian cancer care sector: a rapid scoping review
Bibliographic record
Abstract
BACKGROUND: Despite a publicly-funded healthcare system, alarming cancer-related health and healthcare inequities persist in Canada. However, it remains unclear how equity is being understood and taken up within the Canadian cancer context. Our objective was to identify how health and healthcare equity are being discussed as goals or aims within the cancer care sector in Canada. METHODS: A rapid scoping review was conducted; five biomedical databases, 30 multidisciplinary websites, and Google were searched. We included English-language documents published between 2008 and 2021 that discussed health or healthcare equity in the Canadian cancer context. RESULTS: Of 3860 identified documents, 83 were included for full-text analysis. The prevalence of published and grey equity-oriented literature has increased over time (2008-2014 [n = 20]; 2015-2021 [n = 62]). Only 25% of documents (n = 21) included a definition of health equity. Concepts such as inequity, inequality and disparity were frequently used interchangeably, resulting in conceptual muddling. Only 43% of documents (n = 36) included an explicit health equity goal. Although a suite of actions were described across the cancer control continuum to address equity goals, most were framed as recommendations rather than direct interventions. CONCLUSION: Health and healthcare equity is a growing priority in the cancer care sector; however, conceptual clarity is needed to guide the development of robust equity goals, and the development of sustainable, measurable actions that redress inequities across the cancer control continuum. If we are to advance health and healthcare equity in the cancer care sector, a coordinated and integrated approach will be required to enact transformative and meaningful change.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".