Work-Integrated Learning: An Alternative Pathway for High School Physics
Bibliographic record
Abstract
k2i academy within the Lassonde School of Engineering at York University is committed to dismantling systemic barriers that impact underrepresented youth in science, technology, engineering, and math (STEM), including women, Black youth, and Indigenous youth.A barrier to pursuing engineering and many sciences in post-secondary is high school prerequisite courses, with grade 11 university physics presenting the largest barrier for students, especially those from non-dominant communities.The Bringing STEM to Life: Work-Integrated program addresses this challenge by providing a paid work experience integrated with a high school physics credit for youth who have opted out of physics from underserved communities.The objective is to explore physics fundamentals through hands-on learning that incorporates engineering design and coding, while providing representative mentors from STEM disciplines to create a sense of belonging within STEM spaces.This paper will explore the impact, successes, limitations and next steps for the program and propose how this program might expand to further support deserving communities.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.004 | 0.019 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.030 | 0.007 |
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".