Advancing Pro-Climate Behaviors in Atlantic Canada: Behavioral Insights and Preliminary Evidence
Bibliographic record
Abstract
This symposium explores the multifaceted challenge of fostering pro- climate behaviors and sustainable transportation practices in Atlantic Canada. Showcasing a multi-institutional collaboration among Net Zero Atlantic, the University of Prince Edward Island (UPEI), and the University of New Brunswick (UNB), the symposium integrates behavioral science, evidence-based management, and public policy frameworks to uncover actionable insights for driving environmental sustainability. Characterizing Pro-Climate Behaviours in Atlantic Canada Author: Nicolle Jaramillo; Net Zero Atlantic Driving Toward Sustainability: A Systematic Review and (Potential) Meta-Analysis Author: Lena Jingen Liang; University of Prince Edward Island Author: Xiao Chen; University of Prince Edward Island Exploring Human Motivators for Eco-Friendly Driving Behavior Author: Spencer Lynch; University of Prince Edward Island Author: Xiao Chen; University of Prince Edward Island Author: Lena Jingen Liang; University of Prince Edward Island Navigating Psychological and Structural Barriers to Eco-friendly Driving in Prince Edward Island Author: Jude Imuede; University of Prince Edward Island Author: Lena Jingen Liang; University of Prince Edward Island Author: Xiao Chen; University of Prince Edward Island Overcoming Barriers to Sustainable Transportation: A Study of Pro-Climate Behaviours in Fredericton Author: Jeevitha Palani; University of New Brunswick Public Policy Enablers of Civic Behaviour Change to Reduce GHGs Author: Alex Dandridge; University of New Brunswick
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".