Knowledge Mobilization Intermediaries in STEM: The roles and functions of K-12 STEM Outreach Organizations at Canadian Universities
Bibliographic record
Abstract
Knowledge Mobilization (KMb) is the reciprocal and complementary flow and uptake of research knowledge between knowledge producers, knowledge intermediaries, and knowledge users. The purpose of this investigation is to explore the typology of Canadian university-based Science Technology Engineering and Mathematics outreach organizations and understand if/how they function as knowledge mobilization intermediaries. Three research questions guide this first study; 1) What are the organizational features of K-12 STEM outreach organizations; 2) To what extent do STEM outreach organizations interact with K-12 educators or administration and 3) What knowledge mobilizations processes do they currently use? The methodology used for data collection will be an online questionnaire consisting of qualitative based open-ended questions. The educational importance of this study aligns with the goals of KMb as it has relevance to both within academia and beyond. Within academia, the results will contribute towards the body of knowledge within K-12 STEM education. Beyond academia, this study has value in practice, as the results will engage STEM outreach organizations in conversation about KMb strategies
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.028 | 0.009 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".