Outreach as Research Activism: Using STEM Outreach as a bridge to Social Change
Bibliographic record
Abstract
The STEM Explorers outreach project, headed by a Faculty of Education at a University in Ontario, Canada, brings free, hands-on, and in-community science, technology, engineering, and mathematics (STEM) outreach events to children and their families from groups under-represented in STEM education and careers. The project provides pre-service teachers with experience facilitating inclusive approaches to STEM education and also creates a context to explore their conceptions of activism. The purpose of this phenomenographic research is to describe the experiences of these aspiring teachers to better understand the ways that outreach initiatives can impact their role as STEM education activists. Findings suggest that a positive STEM educator identity, a program of integrated and student-centered STEM learning, and possessing an activist sense of purpose, contribute to the degree to which pre-service teachers regard themselves as STEM education activists.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".