Bibliographic record
Abstract
Abstract In March 1974, trade union leader and Chairman of the Socialist Party of India, George Fernandes, formed a new independent trade union of railway workers and then led a massive nation-wide strike lasting about a month. Two years later—March 1976—Fernandes was arrested as the principal accused in the Baroda Dynamite Conspiracy Case, a plot to bomb strategic targets in New Delhi in resistance to Indira Gandhi’s authoritarian rule. How did George Fernandes’ political work change over these two years—from engaging in traditional trade union movement tactics during the Railway Workers’ Strike in 1974 to being the ringleader of a plan to bomb strategic targets in resistance to the postcolonial state? Why would an activist who advocated non-violent social movement tactics change strategies and end up leading a movement that primarily uses violent tactics? I argue that in its violent repression of the Railway Workers’ Strike and its illegal imprisonment of the strike’s leaders, Indira Gandhi’s administration demonstrated to Fernandes and other opposition party leaders that there was no room for a peaceful solution to the ever increasing social conflict of early 1970s India. Therefore, when Gandhi instated herself as dictator, longstanding advocates ofsatyagrahabelieved that symbolic violence against the state was the tactic most likely to lead to the restoration of democracy in India.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.029 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".