Everyone a Changemaker? Exploring the Moral Underpinnings of Social Innovation Discourse Through Real Utopias
Bibliographic record
Abstract
The term ‘social innovation’ has come to gather all manner of meanings from policymakers and politicians across the political spectrum. But while actors may unproblematically unite around a broad perspective of social innovation as bringing about (positive) social change, we rarely see evidence of a shared vision for the kind of social change that social innovation ought to bring about. Taking inspiration from methods that recognise the utopian thinking inherent in the social innovation concept, we draw upon Erik Olin Wright’s concept of ‘real utopias’ to investigate the moral underpinnings inherent in the public statements of Ashoka, one of the most prominent social innovation actors operating in the world today. We seek to animate discussion on the moral principles that guide social innovation discourse through examining the problems that Ashoka is trying to solve through social innovation, the world they are striving to create, and the strategies they propose to realise their vision.
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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 | 0.051 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.018 | 0.143 |
| Scholarly communication | 0.030 | 0.031 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.011 | 0.015 |
| Insufficient payload (model declined to judge) | 0.004 | 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".