Recognizing and Transforming Knowledge Mobilization in Colleges of Education
Bibliographic record
Abstract
This study examines emerging efforts by three colleges of education to contribute to and benefit research use through public systems of knowledge exchange among researchers, practitioners, policymakers, and other education stakeholders. Often labeled knowledge mobilization (KM), such organization- and individual-level agendas seek to enhance, expand, and sustain engagement with educational research. Colleges of education with public KM agendas signal formal, local efforts at a time when KM remains weakly integrated field- and sector-wide in education. The study therefore illuminates the interdependent opportunities and challenges that accompany individual and organizational capacities for such change. Drawing on faculty survey responses (n=66), findings resolve scholarly practices in terms of both knowledge production and mobilization as well as in relation to individual and organizational agendas, which are considered in terms of four general tensions that influence efforts to extend the reach and impact of scholarship in colleges of education.
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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 | 0.054 | 0.087 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.023 | 0.035 |
| Scholarly communication | 0.028 | 0.009 |
| Open science | 0.003 | 0.042 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".