The Butterfly Effect and Its Cumulative Role in Promoting Social and Political Change in Sudan
Bibliographic record
Abstract
The Butterfly Effect, a concept originating from chaos theory, has been increasingly applied to understanding political and social change, particularly in contexts of repression. This study, focusing on Sudan’s recent history, explores how small, localized actions can catalyze broader social and political transformations. The article integrates primary and secondary data collection methods to understand the Butterfly Effect in grassroots resistance. Data Collection is based on primary and secondary data; the primary data is collected from 15 in-depth interviews with key figures from the Salmiya Group and other grassroots movements. The interviews focused on their strategies, challenges, and perspectives on nonviolent resistance and community mobilization. Participants were selected using purposive sampling, targeting individuals directly involved in resistance efforts to provide detailed insights. Secondary Data Analyzed news articles, reports, and social media content documenting the activities of Sudanese resistance movements. Historical accounts of Sudan’s 2019 revolution and the 2021 military coup were included to contextualize the findings and examine the themes and patterns in resistance strategies, including nonviolent resistance, social media activism, and community mobilization.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".