DECISION MAKERS’ EXPERIENCES OF COLLABORATING WITH RESEARCH TEAMS ON FEDERALLY FUNDED HEALTH RESEARCH INITIATIVES: AN INTERPRETIVE DESCRIPTIVE 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
Consistent with the paradigm of evidence informed decision making we assume that research findings are integrated into health services practice and policy. However, there is a gap betweeen research findings and usual practice. Collaborative research, where researchers are encouraged to partner with decision makers to conduct mutually agreed and relevant research, may facilitate prompt utilization of new findings. My study explored decision makers’ experiences of collaborative teams executing federally funded health research. The principles of interpretive description were used to guide sampling, data collection, and analysis. A purposeful sample of 27 decision makers, collaborating on Partnerships for Health System Improvement (PHSI) projects funded by the Canadian Institutes of Health Research, participated in two in-depth interviews. Conventional content analysis was used to identify concepts. The conceptual framework was developed inductively from the descriptive data and provided a structure for interpreting decision maker perspectives. The framework posits an explanation leading to contextual understanding of their experiences. This study describes factors affecting PHSI engagement that include: availability of new funding; positive history with the researcher; prospect of tangible benefits to constituents of decision makers; desire to contribute to research that informs health services programs and policies; capacity building; and knowledge creation. The partnership process is facilitated by fostering connections; identifying required skills and competencies; maintaining a sustainable focus of inquiry; clarifying roles and responsibilities; cultivating a nurturing learning environment. My findings will inform decision makers, researchers, and funding agencies about the experience and legacy of collaborative 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 | 0.012 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.025 | 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