Pediatric Oncology Knowledge Mobilization in Canada: Protocol for an Environmental Scan
Bibliographic record
Abstract
BACKGROUND: Nonprofit organizations that serve the pediatric oncology community play a crucial role in disseminating quality information that can inform and support people living with childhood cancer, those that work in the field, and others who make key decisions or policies. These registered organizations can be challenging to locate, as the internet is flux with information and resources of varying quality, misinformation, and disinformation. There remains limited understanding of the knowledge mobilization landscape of these organizations in Canada. OBJECTIVE: This study will provide an overview of the pediatric oncology nonprofit organizational landscape and describe their knowledge mobilization efforts related to dissemination, highlighting existing strengths, gaps, and novel opportunities to strengthen and unite efforts. METHODS: A novel environmental scan methodology will be employed to search government and nonprofit organizations' databases. Independent reviewers will screen the websites of eligible organizations. Extracted data will be descriptively analyzed, geographically sorted, and presented in a tabular form with accompanying narrative. RESULTS: This project received funding in 2024. We anticipate that preliminary results will be available by summer 2025. The search strategy for this study will be completed in the spring of 2025. One key project milestone for this environmental scan includes sharing drafts of the results from this strategy through expert consultations in the spring of 2025. After this milestone, a full set of preliminary results will be available by summer 2025, and the final manuscript will be submitted in fall 2025. CONCLUSIONS: The environmental scan will explicate each step of our method to allow others the opportunity to garner understanding from our learnings. Findings will be disseminated to the broader community via social media, directly to the pediatric oncology network in Canada, and globally, through summaries, infographics, presentations, and traditional academic outputs. By doing so, the pediatric oncology community will have information pertinent to navigating these resources, and further steps can be devised to bolster the knowledge mobilization capacity in Canada. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/76787.
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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 | 0.051 | 0.075 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.013 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.131 | 0.020 |
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".