Precarious Workers and the Labour Process: Problematising the Core/Non-core
Bibliographic record
Abstract
This article recentres labour process theory in the analysis of the South African manufacturing sector to challenge the perception that precarious workers in the formal economy are largely “flexible extras” unrelated to the “core” of production. Through case study analysis of two manufacturing workplaces in Gauteng, South Africa, we demonstrate how precarious workers are both core to production and to the production of surplus value. Our analysis demonstrates how employers have increasingly restructured work through reclassifying large parts of the labour process as “non-core”. This trend has accelerated in recent years as employers seek to evade new legal responsibilities following amendments to the Labour Relations Act in 2014. Despite employers’ attempts to redefine the labour of precarious workers as non-core, we demonstrate that these workers nevertheless play an increasingly central role in the valorisation regimes of manufacturing companies – rendering them core to the production of surplus value for manufacturing capital. Our analysis problematises Von Holdt and Webster’s (2005) core/non-core schema for analysing the South African labour force, which locates precarious workers in the formal sector in the non-core. We argue that while this schema has some utility in describing the make-up of the labour force, its abstraction from an analysis of the labour process obscures the fact that precarious work has become central to manufacturing capital’s valorisation strategy. Finally, the article reflects on how precarious workers are attempting to organise within and in parallel to trade unions. This analysis highlights the importance of going beyond analysing trade unions if we are to contribute to rebuilding the labour movement under conditions of precarity. KEYWORDS: labour-process theory; precarious work; surplus value; labour movement; manufacturing; South Africa
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".