Community needs and interests in university–community partnerships for sustainable development
Bibliographic record
Abstract
Purpose This paper aims to examine the broad concept of university–community partnerships as it applies to creating sustainability initiatives. The benefits of university–community partnerships are increasingly recognized, and this paper offers direct insights from community stakeholders on the principles, functions and activities they see as foundational to effective university–community partnerships in northern British Columbia. Design/methodology/approach CommunityStudio was a co-learning partnership that sought to place students into the community and region to collaborate with community/government partners on interdisciplinary projects identified by the city, regional district or other community stakeholders. Through key informant interviews and a thematic analysis, the authors examine the expressed needs that CommunityStudio partners identified as key to ensuring such collaborations are mutually beneficial. Findings Within the community/regional development context of northern British Columbia, community experience highlights the importance of equity and inclusion, flexible programme design and an institutional culture that supports risk taking in teaching and learning as keys to the success of university–community partnerships. Originality/value This work contributes to calls for knowledge-based institutions such as universities to act as catalysts for social innovation within regional contexts outside of major metropolitan urban centres.
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 | 0.013 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.015 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.002 | 0.023 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".