Bibliographic record
Abstract
Abstract Why do social movements take the forms they do? How do activists’ efforts and beliefs interact with the cultural and political contexts in which they work? Why do activists take particular strategic paths, and how do their strategies affect the course and impact of the movement? Social Movements aims to bridge the gap between “political opportunities” theorists who look at the circumstances and effects of social movement efforts and “collective identity theorists” who focus on the reconstruction of meaning and identity through collective action. The volume brings together scholars from a variety of perspectives to consider the intersections of opportunities and identities, structures and cultures, in social movements. Representing a new generation of social movement theory, the contributors build bridges between political opportunities and collective identity paradigms, between analyses of movements’ internal dynamics and their external contexts, between approaches that emphasize structure and those that emphasize culture. They cover a wide range of case studies from both the U.S. and Western Europe as well as from less developed countries. Movements include feminist organizing in the U.S. and India, lesbian/gay movements, revolutionary movements in Burma, the Philippines, and Indonesia, labor campaigns in England and South Africa, civil rights movements, community organizing, political party organizing in Canada, student movements of the left and right, and the Religious Right. Many chapters also pay explicit attention to the dynamics of gender, race, and class in social movements. Combining a variety of perspectives on a wide range of topics, the contributors’ synthetic approach shifts the field of social movements forward in important new directions.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.064 | 0.010 |
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".