The platform discount: Addressing unpaid work as a structural feature of labour platforms
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Digital labour platforms are able to structure work to limit paid working time, extract fees from workers to access labour, and shift costs associated with occupational safety and health (OSH) compliance onto platform workers. We call this unpaid work the ‘platform discount’. Unpaid labour is embedded within platforms’ competitive strategies as platforms operate with labour oversupply while clients use multiple platforms to search for the cheapest option (multi-homing effect). The authors study pathways through law that would limit the incidence of unpaid work by revisiting three areas of the legal framework: working time, safety and health, and access to work/labour intermediation. The authors argue that reclassification, suggested, among others, by the draft Platform Work Directive, can reduce the platform discount for the misclassified workers, but will leave solo self-employed unprotected. The authors explore two possible strategies to reduce the platform discount for the solo self-employed working on labour platforms: 1) a broader understanding of the concept of working conditions on digital labour platforms covering both standard employees and solo self-employed; 2) proceeding area by area, with the extension of occupational safety and health to the solo self-employed on digital labour platforms being the most feasible and promising from a regulatory standpoint.
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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 | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 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 it