Managing multiple logics in partnerships for scaling social innovation
Bibliographic record
Abstract
Purpose The purpose of this paper is to contribute to the field of social innovation by examining institutional logics at the level of inter- and intra-organizational partnerships for scaling impact. Design/methodology/approach The authors use a set of case studies from the Stanford Social Innovation Review to analyze success in scaling social innovations applying the logic compatibility-centrality matrix proposed by Besharov and Smith (2014), which aims to reveal the potential for conflict in organizations based on the diversity of logics present and the degree to which they are compatible with each other. Findings The findings shed insight on how individuals and organizations are able to manage logic multiplicity in the context of partnerships for scaling social innovation. Originality/value The authors build on recent work that recognizes logic multiplicity in social enterprises resulting from their hybrid nature, and the authors add to the existing debate by introducing to the discussion contributions from cognitive theory that help explain why organizational cultures evolve and scale out the way they do.
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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 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.011 | 0.017 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".