Mutualism, class composition, and the reshaping of worker organisation in platform work and the gig economy
Bibliographic record
Abstract
This article contributes an understanding of mutualism as a foundational element in emergent worker collectivism. We challenge mainstream institutionalist accounts in industrial relations, especially from the Global North, that downplay processes of bottom-up regeneration of working-class organisation. We discuss compositional accounts of class formation and examine previous understandings of mutualism, then apply our conceptual framework to evidence from international literature and our own research on platform work in Italy and the UK. Three important themes emerge in understanding worker self-organisation: the demographics of the workforce, including migration backgrounds and social ties beyond the workplace; the existence of social relations in the ethnic/political/local community; and the relevance of free spaces of resource sharing and recomposition in the absence of a fixed place of work. We conclude that an understanding of mutualism can help to grasp emergent solidarities among new groups of workers within and beyond both platform work and trade unions.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".