Taking stock of current societal, political and academic stakeholders in the Canadian healthcare knowledge translation agenda
Bibliographic record
Abstract
BACKGROUND: In the past 15 years, knowledge translation in healthcare has emerged as a multifaceted and complex agenda. Theoretical and polemical discussions, the development of a science to study and measure the effects of translating research evidence into healthcare, and the role of key stakeholders including academe, healthcare decision-makers, the public, and government funding bodies have brought scholarly, organizational, social, and political dimensions to the agenda. OBJECTIVE: This paper discusses the current knowledge translation agenda in Canadian healthcare and how elements in this agenda shape the discovery and translation of health knowledge. DISCUSSION: The current knowledge translation agenda in Canadian healthcare involves the influence of values, priorities, and people; stakes which greatly shape the discovery of research knowledge and how it is or is not instituted in healthcare delivery. As this agenda continues to take shape and direction, ensuring that it is accountable for its influences is essential and should be at the forefront of concern to the Canadian public and healthcare community. This transparency will allow for scrutiny, debate, and improvements in health knowledge discovery and health services delivery.
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.
How this classification was reachedexpand
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 |
|---|---|---|---|
| gpt | MetaresearchScience and technology studiesScholarly communication Domain: Methods · Genre: Commentary About the Canadian research system: yes · About a Canadian topic: yes | Theoretical or conceptual | high |
| grok | MetaresearchScience and technology studiesScholarly communication Domain: Methods · Genre: Commentary About the Canadian research system: yes · About a Canadian topic: yes | Theoretical or conceptual | high |
| opus | Metaresearch Domain: Incentives · Genre: Commentary About the Canadian research system: yes · About a Canadian topic: yes | Theoretical or conceptual | high |
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 | 0.111 | 0.104 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.010 | 0.014 |
| Science and technology studies | 0.054 | 0.039 |
| Scholarly communication | 0.046 | 0.017 |
| Open science | 0.005 | 0.018 |
| Research integrity | 0.015 | 0.017 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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, unvalidatedLabeled directly by 3 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".