Evaluating Social Innovations
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
Social innovations (SIs) frequently bring previously unrelated actors, ideas, and practices together in new configurations with the goal of addressing social needs. However, the dizzying variety of definitions of SI and their dynamic, exploratory character raise dilemmas for evaluators tasked with their evaluations. This article is based on a systematic review of research on evaluation, specifically an analysis of 28 published peer-reviewed empirical studies, within SI contexts. Given that design considerations are becoming increasingly important to evaluators as the complexity of social interventions grows, our objectives were to identify influences on design of evaluations of SI and clarify, which SI features should be taken into account when designing evaluations. We ultimately developed a conceptual framework to aid evaluators in recognizing some differences between SI and conventional social interventions, and correspondingly, implications for evaluation design. This framework is discussed in terms of its implications for ongoing research and practice.
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 | 0.032 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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