Understanding cancer screening experiences of Métis people in Alberta
Bibliographic record
Abstract
Cancer screening is a high priority within the Métis community in Alberta. Despite comparable cancer incidence rates to non-Métis Albertans, Métis people face barriers to accessing cancer screening programs. This study used community-based research approaches informed by Métis ways of knowing to engage 31 individuals across Alberta about their experiences with accessing cancer screening services. Data collection was completed through two in-person Métis gatherings and six telephone interviews. Gatherings included talking circles and cultural activities, with discussions lasting approximately three hours. Topics discussed included experiences with accessing screening services, the quality of care received during appointments, and the supports needed to improve access to screening programs. Discussions were audio-recorded, transcribed, de-identified, and thematically analyzed using NVivo Software. Four prominent themes emerged from this study: (1) the impact of patient-provider communications on cancer experiences, (2) a broken healthcare system and access to care, (3) a need for support and safety, and (4) health promotion behaviours. An overarching theme of discrimination as a social determinant of health emerged throughout the findings. Tangible barriers, including geographical, transportation, and financial, were also identified by study participants. This study provides an increased understanding of Métis experiences related to cancer screening and offers direction for improvements.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".