WHAT FACTORS INDUCE CANADIAN HEALTH ORGANIZATIONS' MANAGERS AND PROFESSIONALS TO USE RESEARCH RESULTS? - A PATH ANALYSIS MODEL
Bibliographic record
Abstract
The aim of this paper is to study direct and indirect effects among variables involved in knowledge utilization explanations. Based on a survey of 928 HSOs ’ managers and professionals of Canadian health organizations (ministries, regional health authorities, hospitals), the results of the path analysis indicate that the research utilization can be explained by different categories of determinants borrowed from absorptive capacity, learning and cultural explanations. The results show that factors explaining the research utilization vary from a type of organization to another and allow us to derive various implications for public planners aiming at the calibration of customized public policies for each of the three types of Canadian health organization. In terms of theory building, the paper refines the organizational perspective of the study of knowledge utilization and shows that utilization processes are interdependent in their causes and effects, and thus complicated to study. Finally, it points out the usefulness of concepts inspired from the organizational theory to explain knowledge utilization.
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How this classification was reachedexpand
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 | 0.010 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 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, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".