Perspectives and Experiences of Canadian Pediatric Rare Disease Researchers in Collaborative Research with Industry: A Mixed Methods Study
Bibliographic record
Abstract
Objectives: We investigated pediatric rare disease researchers’ experiences and perspectives with research collaborations involving industry partners. Methods: This mixed methods study included a cross-sectional survey of academic/hospital-based Canadian pediatric rare disease researchers which informed semi-structured interviews with a subsample of survey participants. We analyzed survey data descriptively and interview data thematically, integrating findings narratively. Results: Of 126 survey respondents, 59 (47%) reported research collaborations with industry; we interviewed 10 of these researchers. Important benefits to collaborations with industry reported by survey participants and interviewees included access to funding and resources, while disadvantages stemmed from perceptions that partners had different motivations. Interviewees provided advice for future researchers including careful selection of an industry partner, relationship building, clear expectations, and utilizing supportive institutional structures. Conclusion: Our findings provide insights into the experiences of pediatric rare disease researchers and offer suggestions on how to conduct successful collaborative research with industry.
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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 | 0.033 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.028 | 0.009 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".