Pilot Study: Student Experience of Climate Change Anxiety and Student Inclination Toward Ethical Behaviour
Bibliographic record
Abstract
It is well established that climate change affects the emotional and psychological health of some individuals, with anxiety being a frequent presentation of the experience and anticipation of climate change. Engineers regularly engage with climate change topics as technology plays a significant role in the human adaptation to, and mitigation of, climate change throughout Canada and beyond. Professional engineers are also held to a high standard of ethics that holds paramount the health, safety, and wellbeing of the public, a requirement that may conflict with opportunities for personal, financial enrichment. In this pilot study, we explore correlations of anxiety and the experience of climate change on engineering student proclivity toward ethical behaviour. Preliminary results from a small cohort of participants show complex interactions between perceptions and experience of climate change and attitudes toward engineering ethics, with several archetypes proposed to serve as a foundation for a larger study. Understanding the influence of climate change on ethical behaviour and sources of student anxiety can help guide engineering educational practice toward greater effectiveness in a changing sociocultural environment.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".