A Tool to Assess and Compare Knowledge Mobilization Efforts of Faculties of Education, Research Brokering Organizations, Ministries of Education, and School Districts
Bibliographic record
Abstract
There are few tools that exist to measure knowledge mobilization (KMb), the process of connecting research to policy and practice, across diverse organizations and sectors. This article reports on a comparison of KMb efforts of 105 educational organizations: faculties of education (N = 21), intermediary organizations (N = 44), school districts (N = 14), and ministries of education (N = 26). This study used an instrument that analyzed KMb efforts along two dimensions -- (1) research dissemination strategies (products, events, and networks) and (2) research use indicators (different types of indicators, ease of use, accessibility, collaboration, and mission) – using data available on organizational websites. Findings: Intermediaries and faculties of education are producing stronger efforts in relation to knowledge mobilization than school districts and ministries of education; however, even faculties and intermediaries generally have modest efforts. Most KMb efforts are product based, with network strategies usually being the weakest KMb strategy utilized.
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How this classification was reachedexpand
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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".