Creating space for sustainability literacy: the case of student-centered symposia
Bibliographic record
Abstract
Purpose This paper reflects on the Sustainability Research Symposium (SRS), a long-term student-led initiative (seven years) at McGill University in Montréal, Canada, that seeks to foster interdisciplinary dialogue among students and researchers by using the sustainability sciences as a bridge concept. The purpose of this study is to explore the effectiveness of the SRS in fostering sustainability literacy. Design/methodology/approach Past participants of the SRS were invited to complete a survey to gauge the strengths and weaknesses of the symposia from a participants’ perspective. A mix of descriptive statistics and axial and thematic coding were used to analyze survey responses ( n = 56). This study links theory and practice to explore the outcomes of symposia as tools for students to engage with sustainability research in university campuses. Findings Survey findings indicated that participants are from multiple disciplinary backgrounds and that they are often interested in sustainability research without being identified as sustainability researchers. Overall, the survey findings suggested that student-organized symposia can be effective mechanisms to enhance exposure to interdisciplinary research and to integrate sustainability sciences outside the classroom. Practical implications Despite being a one-day event, the survey findings suggest that symposia can offer an “initiation” toward interdisciplinary dialogue and around sustainability research that can have lasting impacts beyond the time frame of the event. Originality/value Although research symposia are widespread in university campuses, there is little published information on the effectiveness of student-organized symposia as vectors for sustainability literacy. This original contribution presents a case study of the effectiveness of an annual symposium at one Canadian university, organized by students from the Faculties of Science, Arts and Management.
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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 | 0.018 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.014 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.004 | 0.023 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".