Social Innovations and Crises: Avenues for Reflection and Action from Our 2021 CRISES International Conference
Bibliographic record
Abstract
This review article draws connections between ideas expressed in some key presentations of the 6th International Conference of the Centre for Research on Social Innovations (CRISES). First, in reference to the lectures of Nancy Fraser and Lo c Blondiaux, we discuss the interconnectedness of crises (democratic, economic, ecological, and now sanitary). Then, in relation to the lecture by Janice Fine and the one by Dominique M da and Julie Battilana, we review transformations in the world of work and the challenges it faces in terms of social and environmental justice. Finally, in reference to the lectures of Flor Avelino and of Jean-Baptiste Comby, which we set up in dialogue with each other, we examine the capacity of social innovations to reproduce or transform power relations. We conclude our overview by drawing our own conclusions on what these analyses mean for our workas researchers.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.008 | 0.022 |
| Scholarly communication | 0.023 | 0.025 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.016 | 0.018 |
| Insufficient payload (model declined to judge) | 0.007 | 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".