Bibliographic record
Abstract
Social innovation is about solving important problems in new ways. In professional exchange fields, however, structuring and constraining forces make introducing new solutions exceedingly difficult, and known pathways that introduce new solutions are unlikely to be successful. In this article, I examine how social innovation can be encouraged in a professional exchange field. I identify three kinds of disrupting action (entwining problems, reconfiguring arrangements, and actively waiting) that can be used to encourage social innovation. These actions interrupt and expand essential elements of professionals’ work and they condition parts of the field to be supportive of and susceptible to social innovation. This research contributes to literature in three ways. First, it examines social innovation in a setting that has not been explored, uncovering an amalgamation of pathways that encourage social innovation. Second, it describes three types of disrupting action that set pathways in motion. Third, it conceptually links disrupting action to social innovation.
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.
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 | 0.018 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.017 | 0.026 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.001 | 0.016 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".