Defining social innovation for post-secondary educational institutions: a concept analysis
Bibliographic record
Abstract
Abstract Education, research, and contribution to society through innovation are the three missions of post-secondary educational institutions. There is a gap in understanding the concept of social innovation for post-second educational institutions. A clear definition would: (a) guide institutional strategic direction and supports, (b) recognize and reward academic research in social innovation, and (c) enable accurate measurement of outcomes and impact of social innovation activities. To redress the definitional imprecision, Walker and Avant’s method was used to conduct a concept analysis of social innovation. Four multi-disciplinary databases were searched to identify 1830 records. Antecedents, defining attributes, and consequences of social innovation were extracted from 272 of these articles. Defining attributes were reconstructed to develop a new definition. For post-secondary educational institutions, social innovation was defined as the intentional implementation of a transdisciplinary initiative to address a social challenge enabled through collaborative action leading to new or improved capabilities and relationships with community to generate evidence-informed solutions that are more effective, efficient, just, and sustainable. With greater clarity about the definition of social innovation, post-secondary educational institutions can create strategic plans and allocate resources to fulfil the Third Mission. With an evidence-informed definition, post-secondary educational institutions can develop a measurement framework to demonstrate outcomes and impacts of social innovation.
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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 | 0.023 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.033 | 0.027 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".