Protest Camps and Repertoires of Contention
Bibliographic record
Abstract
Protest camps have become a prominent feature of the post-2010 cycle of social movements and while they have gripped the public and media's imagination, the phenomenon of protest camping is not new. The practice and performance of creating protest camps has a rich history, which has evolved through multiple movements, from Anti-Apartheid to Anti-war. However, until recently, the history of the protest camp as part of the repertoire of social movements and as a site for the evolution of a social movement's repertoire has largely been confined to the histories of individual movements. Consequently, connections between movements, between camps and the significance of the protest camp itself have been overlooked. In this research profile, we argue for the importance of studying protest camps in relation to social movements and the evolution of repertoires noting how protest camps adapt infrastructures and practices from tent cities, festival cultures, squatting communities and land-based autonomous movements. We also acknowledge protest camps as key sites in which a variety of repertoires of contention are developed, tried and tested, diffused or sometimes dismissed. To facilitate the study protest camps we suggest a theory and practice of ‘infrastructural analysis’ and differentiated between four protest camp infrastructures: (1) media & communication, (2) action, (3) governance and (4) re-creation. We then use the infrastructures of media and communications as a brief example as to how our proposed infrastructural analysis can contribute to the study of repertoires and our understanding of the rich dynamics of a protest camp.
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 | 0.009 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.011 | 0.039 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".