Canada and India: An Innovative Partnership to Advance Oncology Nursing Research
Bibliographic record
Abstract
Cancer care nursing research is at a very promising juncture in the history of the field. This is a result, in part, of the unprecedented availability of funding for research, continuing education, clinical training, and, more recently, well-funded research training opportunities for nurses interested in pursuing graduate work in oncology nursing. Canada and India have been at the forefront of establishing two well-articulated research programs to train the next generation of clinician-researchers in the area of psychosocial oncology. The initiatives have been particularly timely because wide access to information technology allows the transcendence of time and geographic boundaries to bring relevant stakeholders together to advance the science and practice of oncology nursing. The purpose of this article is to review the specific research training activities (a core videoconferenced evidence-based seminar; periodic virtual, interactive brainstorming sessions; and yearly face-to-face workshops) of the programs in terms of core themes and pragmatic issues associated with their delivery across the various national and international training sites. Strategies are presented to ensure that research training activities can be replicated across other clinical sites, institutions, and countries. This article hopefully will inspire other researchers to develop similar transdiscipinary research training programs toward a strong research and mentoring tradition within nursing and across relevant psychosocial oncology fields.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".