Principles and related strategies for spinal cord injury research partnership approaches: a qualitative study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Conducting and/or disseminating research in partnership with potential research users is a popular approach to conducting useful and relevant research. Despite calls for guidance to support these research partnerships, evidence-based tools and resources remain limited. Aims and objectives: This study aimed to explore principles and related strategies for conducting and/or disseminating spinal cord injury (SCI) research in partnership with the SCI community, in order to gain insight into ways to support SCI research partnerships. This qualitative study included ten semi-structured interviews with SCI research partnership champions. The interviews focused on participants’ experiences with SCI research projects that are conducted or disseminated in partnership, and related principles and strategies to work in research partnerships. Participants mainly talked about principles related to: (1) the relationship between researchers and research users (for example, respect each other, avoid tokenism); (2) co-production of knowledge (for example, research user engagement early and throughout ); and (3) meaningful engagement (for example, allowing flexibility). Examples of related strategies included attending collaborative conferences, research user engagement in refinement of research questions, training in research methods, and hiring people with SCI as part of the research team. Key conclusions: This qualitative study presents research partnership principles (norms) and related strategies (observable actions). This study can provide guidance for other researchers and research users who want to engage in (SCI) research partnerships. The findings of this study could be used to inform the development of evidence-based tools and resources to support future research partnerships.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.019 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it