Why Local Social Forums Emerge Where They do: Beyond Diffusion, Geographical Appropriation
Bibliographic record
Abstract
Abstract Social forums are, quintessentially, a transnationally mobile institutional enterprise. Since the first World Social Forum in Porto Alegre, Brazil, in 2001, thousands of local initiatives have emerged all over the world. Yet we know very little about the diffusion processes involved. This article examines nine local social forums (LSFs) in two societies (France and Québec) in order to understand how social forums (SFs) spread throughout or within each territory. Aside from the usual factors, such as the presence or absence of an initiator, favorable political opportunity structure and access to resources, I consider the geography of appropriation, with an emphasis on the dimensions of place (where the forums are organized), and scales of action built by activists. First, I show that, as proposed in the social movement literature, SFs spread from the global South to the global North as a direct result of activists willing to reproduce within their localities that which they have seen and experienced on a larger scale. Political opportunity structures and access to resources appear relevant to understanding the longevity of LSFs and their capacity to be more or less encompassing experiences. But beyond these ‘usual suspects’, the geographical appropriation of social forums is an important consideration that helps us understand the specific diffusion of LSFs in each national territory. In Québec, the region is perceived as a ‘given’ by activists and becomes the relevant scale of collective action, while in France, scale building is at stake and LSFs are used as a tool to escape the centralization of the main national organization in the field of global protest.
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 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.018 |
| Scholarly communication | 0.014 | 0.014 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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".