Empowering Youth for Climate Action: Implementing a Locally-Focused Health Effects of Climate Change Curriculum in Baltimore Public Schools
Bibliographic record
Abstract
Introduction: Given global climate change, it's crucial to mitigate immediate and long-term health risks through initiatives that foster advocacy for a healthier climate and improved human health. This research presents a feasibility study of the Health Effects of Climate Change Curriculum (HECCC), an intervention aimed at enhancing climate literacy and empowering youth to become climate-health activists in primary and secondary public schools in Baltimore City and County. Methods: The HECCC was developed by a multidisciplinary team and consists of the following lessons: (1) Introduction to Climate Change, (2) Air Quality and Weather, (3) Food and Water, and (4) Environmental Justice and Health Equity. Lessons were taught in-person, during school hours, by trained pre-health students and healthcare professionals. Schools were invited to participate based on prior engagement in our health education initiatives, building upon pre-existing community partnerships. Results: From Spring 2023 to Spring 2024, the HECCC was implemented in four public and secondary public schools throughout Baltimore City and County, reaching approximately 300 students between ages 9 to 18. All schools were composed of predominantly non-white students, and located in areas with unique climate change vulnerabilities and healthcare clinician shortages. Teacher feedback at all schools indicated enjoyment of the curriculum, perceived expansion of students' knowledge, and increased interest in the health effects of climate change. Conclusions: This study demonstrates the feasibility of a community-based, locally-focused climate change and health curriculum that can be adapted for various ages and class durations. Future steps involve refining the curriculum and expanding to more schools.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".