Student‐led campus climate change initiatives in Canada
Bibliographic record
Abstract
Purpose The purpose of this paper is to provide a comprehensive list of student‐led, campus‐based climate change initiatives, and offers details on many specific cases. The paper also documents the roles students have played and considers the larger youth engagement implications. Many of these initiatives can be replicated elsewhere, thereby providing a starting point for students wanting to begin an initiative or providing ideas for other campus stakeholders wanting to engage students in initiatives. Design/methodology/approach Campus reports were collected by the Sierra Youth Coalition from 65 Canadian Universities and Colleges. This qualitative information was coded for student‐led climate‐related initiatives, and for the roles students played in those initiatives. The patterns were identified and clustered, and are presented in this paper. Findings Students were found to be successfully leading eight different types of campus climate change‐related initiatives, both with the support of other campus stakeholders and without this support. Students were also found to be able to successfully take on a variety of types of leadership roles in these initiatives. Youth engagement ranged from socialization to influence to power, depending on the type of initiative. Research limitations/implications A limitation of this research is that only 65 of the approximately 227 colleges and universities in Canada participated. Also, it is possible that some schools may not have reported all student‐led initiatives, or all the student roles. In addition, the data were limited to the 2007/2008 academic year, so is limited to the initiatives which occurred in that year. Originality/value This paper presents different types of student‐led climate change initiatives, the roles students have played in these initiatives, and the implications for youth engagement in creating climate change solutions. It contributes to the climate change, the campus sustainability, and the social movements literatures.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".