Local Dynamics as a Resource for Labour Protests: The Case of Wildcat Strikes in the Metal Industry in Turkey, 2012-2016
Bibliographic record
Abstract
This article analyses the role of local dynamics on trade unions’ mobilisation capacity at thenational level, with a focus on the wildcat strikes in the metal sector in Bursa, a city in north-westTurkey, from 2012 to 2016. It studies to what extent local dynamics such as alliances with localbranches of political parties, workplace demonstrations, and local electoral and union organisingcampaigns contributed to protests against national government policies. The research andanalysis are based on both qualitative data collected during fieldwork and on quantitative datafrom a variety of Turkish and international sources. Through an analysis of the wildcat strikes,the article contributes to the literature on labour movements and strikes in authoritarian contexts.Differently from the majority of the existing literature on this issue, it focuses on the workplacelevel rather than analysing the relations between government officials and the trade unionconfederations at the national level. By doing this, it shows that, despite the oppressive context atthe national level, trade unions may regain power at the sectoral level.KEYWORDS: trade unions; metal industry; Turkey; authoritarian regime; social movements
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".