Transforming research systems for meaningful engagement: a reflexive thematic analysis of spinal cord injury researchers’ barriers and facilitators to using the integrated knowledge translation guiding principles
Bibliographic record
Abstract
PURPOSE: To develop an in-depth understanding of spinal cord injury (SCI) researchers' barriers and facilitators to deciding to use 1) a partnered approach to research and, 2) systematically developed principles for guiding Integrated Knowledge Translation (IKT) in spinal cord injury research (IKT Guiding Principles). METHODS: Qualitative interview study with North American SCI researchers who were interested in using a partnered research approach. The research was conducted using an IKT approach, and interview data were analyzed using reflexive thematic analysis. RESULTS: Thirteen SCI researchers whose research focused on prevention, clinical, rehabilitation, and/or community SCI research were interviewed. Three themes were co-constructed with partners: 1) the principles are necessary but not sufficient for the implementation of a partnered approach to research; 2) relational capacity building is needed; and 3) institutional transformation is needed to value, resource, and support meaningful engagement. CONCLUSIONS: ). Findings provide clear, practical, and tangible actions to promote change that can support meaningful engagement in the SCI Research System.
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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 | 0.246 | 0.230 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.016 | 0.030 |
| Scholarly communication | 0.015 | 0.016 |
| Open science | 0.004 | 0.019 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".