Whose Responsibility Is It? Implementing Patient-Prioritized Healthcare System Change in Oncology
Bibliographic record
Abstract
This brief commentary describes the reflections on a fundamental question by the Public Interest Group on Cancer Research, a successful academic-community partnership focused on cancer research, education, public engagement, and advocacy in Canada's Eastern province of Newfoundland and Labrador. Our Group has achieved some success in a short time with very limited funding. It has successfully created public spaces for conversations about cancer care and priorities for research and regularly advocated for health service change prioritized by input from patients and family members. However, we remain challenged in our understanding of how to truly implement change within oncology care contexts that is informed by patients and families affected by cancer. In this short reflection, we hope to raise awareness of this important issue and question whose responsibility it is to work with patients and families and follow through on prioritized healthcare issues and services. We suggest this may be a matter of integrated knowledge translation and a better understanding of where patients and families fit in this space. We hope to encourage reflection and conversation among all relevant stakeholders about how best to implement patient-prioritized change in oncology care and policy.
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 | 0.056 | 0.089 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.031 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.017 | 0.025 |
| Insufficient payload (model declined to judge) | 0.004 | 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".