Integrated Knowledge Translation with Public Health Policy Makers: A Scoping Review
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
Integrated knowledge translation (iKT) refers to the engagement of knowledge users (e.g., policy makers, clinicians, patients) as active participants in the research process. Theoretically, this involvement enhances research relevancy and usefulness, thereby supporting health system change. However, evidence to support best practices for iKT is lacking, particularly in a public health context and with non-clinical decision-makers. The objectives of this research were to report how decision-maker involvement in public health iKT research has been described and operationalized and whether the process was evaluated. We conducted a scoping review of published literature from January 2005 to December 2017 and extracted information related to iKT involvement, barriers and facilitators and outcomes. Studies typically did not distinguish between different kinds of knowledge users, making it impossible to comment specifically on decision-makers' involvement. Authors believed knowledge user involvement was beneficial to the quality and potential impact of research activities, although corroborating evaluation data were unavailable. Broad research-knowledge user partnerships spanning multiple projects, as well as flexible involvement of knowledge users, enhanced engagement and supported the iKT process.
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.
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
| gpt | Scholarly communicationMetaresearch Domain: Methods · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | medium |
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 | 0.010 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 0.005 |
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