Winning Conditions of Precarious Workers’ Struggles: A Reflection Based on Case Studies from South Korea
Bibliographic record
Abstract
In South Korea, many struggles of non-regular workers, who attempted to organize their unions and engage in militant action to protest against employers’ inhumane discrimination and illegal exclusion, have failed to achieve the desired outcomes, due to their vulnerable employment status and their lack of action resources. In this light, our study examines the conditions that lead to victory in precarious workers’ struggles, by focusing on three attributes: internal solidarity with regular workers, external solidarity from labour and civil society groups outside the workplace, and mobilized protest repertoires. Specifically, this study seeks to identify the configurations of these three conditions that produce successful outcomes in precarious workers’ struggles, in terms of bargaining gains and organizational sustainability. We do this by employing fs/QCA modelling to examine 30 major cases of non-regular worker struggles occurring over a 16-year period from 1998 to 2013. Our analysis presents the finding that the conditional configuration of strong external solidarity, strong internal solidarity, and fewer struggle repertoires constitutes a significant causal path to successful outcomes. This reaffirms the idea that strong solidarity bridging, whether with regular workers that have a different employment status in the segmented workplace, or with labour and civil society groups outside the workplace, is the crucial causal condition for precarious workers to achieve their desired outcomes from struggle. An unexpected finding, however, is that when precarious worker struggles mobilize fewer struggle repertoires, they are likely to achieve the successful outcomes of bargaining and organizational gains. Our study contributes to the theoretical elaboration of labour movement revitalization for the precariat class, by shedding light on the activism of precarious workers, considering that the English-language literature that pays attention to the active role of such atypical workers in staging protests against employers’ inhumane treatments and the neoliberal labour regime is limited.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".