Establishing and sustaining authentic organizational partnerships in childhood disability research: lessons learned
Bibliographic record
Abstract
There is an increased interest from both researchers and knowledge users to partner in research to generate meaningful research ideas, implement research projects, and disseminate research findings. There is accumulating research evidence to suggest the benefits of engaging children/youth with disabilities and their parents/families in research partnerships; however, less is known about the benefits of, and challenges to, engaging organizations as partners in research. The purpose of this commentary is to reflect on successful organizational partnership experiences from the perspectives of researchers at an internationally-recognized childhood disability research centre (CanChild), and to identify and share key ingredients for developing partnerships between organizations and academic institutions. A companion study is underway to examine partnership experiences with CanChild from the partners' perspective. Four CanChild researchers and two co-facilitators participated in a collaborative auto-ethnography approach to share experiences with organizational research partnerships and to reflect, interpret, and synthesize common themes and lessons learned. The researchers and facilitators met virtually via Zoom for 105 min. Researchers were asked to discuss the following: the formation of their organizational partnerships; if/how partnerships evolved over time; if/how partnerships were sustained; and lessons learned about benefits and challenges to building research partnerships with organizations. The meeting was recorded, transcribed verbatim, and analyzed by the facilitators to identify and synthesize common experiences and reflections. Multiple rounds of asynchronous reflection and feedback supported refinement of the final set of analytic themes. Researchers agreed that partnerships with organizations should be formed through a mutual interest, and that partnerships evolved by branching to include new organizations and researchers, while also involving trainees. Researchers identified the importance of defining roles and responsibilities of key individuals within each partnering group to sustain the partnership. Lessons learned from organizational partnerships included reciprocity between the partnering organization and academic institution, leveraging small pockets of funds to sustain a partnership over time, and building a strong rapport with individuals in a partnership. This commentary summarized lessons-learned and provided recommendations for researchers and organizations to consider when forming, growing, and sustaining research partnerships over time.
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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 | 0.047 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.012 |
| 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; 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".