Professional navigation: A comparative study of two Canadian models
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
For many cancer control programs, cancer navigation has emerged as a specific strategy to improve access to supportive care and the patients' experience of cancer care. This study contributes to a better understanding of professional navigation by comparing two Canadian models: Quebec's Pivot Nurse in Oncology (PNO) and Nova Scotia's Cancer Patient Navigator (CPN). Qualitative interviews were conducted with professional navigators, patients and family members, front-line staff, physicians and health administrators (interviews: n = 49; focus groups: n = 10). The two models were analyzed using the professional navigation framework (Fillion et al., 2012). Although the models are different, results show that professional navigators in both programs perform similar functions and face similar challenges. This study highlights the complexity and the value of cancer navigation and recommends relevant actions to optimize its management within the health care system.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 it