Climate change education: the need for comprehensive climate change education in environmental public health curriculum
Bibliographic record
Abstract
Climate change is a significant issue impacting human and environmental health. Public health professionals will play an important role in responding to this crisis. This research investigated the need for enhanced climate change education for those in a Canadian Institute of Public Health Inspector (CIPHI)-accredited post-secondary program. In February 2020, a web-based survey was sent to public health professionals via the Ontario Branch of the CIPHI and the Association of Supervisors of Public Health Inspectors in Ontario listservs. The survey explored the climate change subject areas most relevant to public health work, reflections of public health professionals’ own climate change education, and opportunities for improvements in climate change education. The results showed most public health professionals are aware of climate change’s relationship to human health, recognize its impacts in their field, and believe in the value of climate change education. Understanding climate change impacts within this public health profession and the need for climate change education can influence future curricula for prospective public health professionals, resulting in professionals entering the field prepared to tackle the challenges of the future.
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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 | 0.007 | 0.008 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".