Making Sense of Social Change: Observing Collective Action in Networked Cultures
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract This article presents an overview of rising trends in the study of networked interactions conveyed by social media technologies and the emergence of new meanings associated with social change. In recent years, a healthy amount of studies has focused on ICT uses within collective action, considering social media tools to have become crucial components of many transnational movements and social change projects. Crossing boundaries between social movements theories, political science, and communication studies, literature suggests that ‘online activism’ and increasingly networked interactions may have transformed the meanings and definitions associated with ‘collective action’ and ‘social change’. To make sense of these meanings, we identify three approaches used by scholars, which focus on (i) the actual networking of actors, (ii) the diffusion of new repertoires and frames through networks, and (iii) making sense of new meanings conveyed within networked cultures . We conclude by suggesting the need for more comprehensive research to better observe and make sense of how's actors define collective action and how they use social media tools when striving to convey social change.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it