HEI as a pressure cooker: crafting the secret sauce to social justice in social innovation
Bibliographic record
Abstract
Purpose This paper aims to reflect on the facilitative factors that contribute to a shift in focus to social innovation for social justice in a higher education institution. The study provides lessons learned that can be takeaways for others interested in shifting their conceptualization of social innovation toward social justice. Design/methodology/approach Relying on a case study of social innovation at Ryerson University, the paper begins with a brief history and the later development of the Office of Social Innovation. Through a reflection on three key initiatives, the study discusses strategic planning and partnerships, student programming and communications strategy. Findings The reflection process provides ingredients that have facilitated the intentional grounding of social innovation offerings and practices in social justice values, including creativity, collaboration, adaptability, voice and shifting the spotlight to alternate stories and ways of understanding social innovation. The authors also discuss the role of generative conflict and contradictions. Originality/value This study presents a reflective case study from a public research university, which holds a prominent reputation in entrepreneurial incubators and curricular offerings. With candid reflections from faculty and staff central in strategizing the direction of social innovation, the authors present experiences, perspectives and conflicts encountered when challenging the language and application of social innovation. The result is a unique contribution on what it means to ground post-secondary social innovation in social justice, why this shift was necessary and what has come from this work.
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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 | 0.015 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.016 | 0.053 |
| Scholarly communication | 0.016 | 0.016 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".