Five Configurations for Scaling Up Social Innovation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Why do so many social innovations fail to have a broad impact? Successful social entrepreneurs and nonprofit organizations often “scale out” innovative solutions to local problems in order to affect more communities or numbers of individuals. When faced with institutional barriers, they are motivated to “scale up” their efforts to challenge the broader institutional rules that created the problem. In doing so, they must reorient their own and their organizations’ strategies, becoming institutional entrepreneurs in the process. This article proposes a contextual model of pathways for system change consisting of five different configurations of key variables and informed by qualitative interview data from selected nonprofit organizations. The authors argue that the journey from social to institutional entrepreneurship takes different configurations depending on the initial conditions of the innovative initiatives. Despite an expressed desire to engage in system change, efforts are often handicapped by the variables encountered during implementation.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it