Practices of Local Social Forums: The Building of Tactical and Cultural Collective Action Repertoires
Bibliographic record
Abstract
Since the first edition of the World Social Forum in Porto Alegre, Brazil, 2001, similar initiatives have flourished at the local scales. In the existing literature, local social forums are generally considered to be a natural replication of the world social forums. Beyond the label “social forums,” what do the practices of local social forums specifically entail and what is the meaning of these practices for local activists?I propose a comparison of eight cases situated in two distinct societies (Quebec and France). I use a multi-approach methodology, combining direct observation, focus groups, interviews, and documentary analysis.I show that despite strong national differences, a highly decentralized process, and the strong autonomy of local actors, local social forums share structural characteristics, and the expression “social forum” is associated with ways of doing things that limit the variety of local social forum initiatives: organizers share a common intentionality; the mode of operation of local social forum process and event belong to the same political culture and translate into the same practices; and the outputs of these gatherings are similar in terms of the building of ties. Overall, local social forums are used as tactical and cultural collective action repertoires by actors, redefining the boundaries of social resistance and its practices.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.008 | 0.035 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".