Combining forces
Bibliographic record
Abstract
Purpose This paper describes the sustainability partnership between the City of Vancouver and the University of British Columbia (UBC) and, in particular, the co-curricular Greenest City Scholars graduate student internship program, which has been developed by the two organizations. Through the program, UBC graduate students work on projects at the City that help to advance sustainability targets. The paper aims to explore the successes, challenges and lessons learned from the program. Design/methodology/approach This case study uses literature and document review, observations, program participant evaluation surveys and project impact survey feedback. Findings The Greenest City Scholars program model has contributed to the sustainability goals at UBC and the City of Vancouver and has supported the partnership between the two organizations. The program has grown over its five-year history and is considered to be a central part of the partnership. Breadth of student participants from across the university and high participation from City departments have been achieved. The model is now being adapted to be delivered within other partnerships. Practical implications The experiences presented in this case study can help other higher education institutions understand how a co-curricular graduate student work experience program could help to bolster their own sustainability partnerships. Originality/value This paper makes a contribution by providing insight into the use of a graduate student program to advance the goals of a university–community sustainability partnership.
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 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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.005 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.215 | 0.052 |
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".