Uncovering Micro‐Practices and Pathways of Engagement That Scale Up Social‐Driven Collaborations: A Practice View of Power
Bibliographic record
Abstract
Abstract This paper explores how large‐scale social‐driven collaborations might grow in scale and help promote political change. We present the results of a qualitative investigation of a complex platform where multiple and hybrid collaborations co‐exist and where civil society plays a central role. Based on a longitudinal comparative case study, we draw a processual model describing micro‐practices and pathways of engagement. We show that the emergence of these collaborations requires a new type of convener, one that is able to manage the interplay between the sharing/co‐creation of abundant resources and the coordinated decentralization of informal authority. Our study extends existing debates on the role of resources and authority, showing the complementarity between possession and practice perspectives of power. Finally, we identified synergies between collaboration and social movement literatures, particularly showing that large‐scale collaborations could be mobilized to refine social movement agendas and achieve more purposive collective action.
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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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.029 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".