SU‐F‐E‐08: Medical Physics as a Teaching Tool for High School Science Curriculum
Bibliographic record
Abstract
Purpose: Delivering high school science curriculum in a timely manner and in way that is accessible to all students is a challenge for teachers. Although many high schools offer career workshops, these are typically directed at senior students and do not relate directly to details of the curriculum. The objective of this initiative was to create a series of lectures that use medical physics to relate many aspects of the high school science curriculum to tangible clinical applications and to introduce students to alternate pathways into a career in health sciences. Methods: A series of lectures has been developed based on the Ontario High School Science Curriculum. Each lecture uses a career in radiotherapy medical physics as the framework for discussion of topics specific to the high school course being addressed. Results: At present, these lectures have been delivered in five area high schools to students ranging from sophomores to seniors. Survey documents are given to the students before and after the lecture to assess their awareness of careers in health care, applications of physics and their general interest in the subject areas. As expected, students have limited up front awareness of the wide variety of health related career paths. The idea of combining a career lecture with topics specific to the classroom curriculum has been well‐received by teachers and students alike. Conclusion: Career talks for high school students are useful for students contemplating their post‐ secondary career path. Relating career discussion with direct course curriculum makes their studies more relevant and engaging. Students aspiring to a career in health sciences often focus their studies on life sciences due to limited knowledge of potential careers. An early introduction to medical physics presents them with an alternate path through the physical sciences into health care.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.041 | 0.010 |
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".