‘Not the usual gig’: The personal scope(s) of application of Directive 2024/2831 on improving working conditions in platform work
Bibliographic record
Abstract
This article examines the complex and innovative personal scope of the EU Platform Work Directive 2024/2831, highlighting its dual framing around the concepts of ‘platform workers’ and the broader category of ‘persons performing platform work’. The authors explore how the Directive partially departs from traditional binary distinctions between employees and self-employed persons by introducing a more nuanced regulatory approach anchored in both labour law and data protection law. The article analyses the scope of key provisions of the Directive, showing how it confers many protections beyond the confines of the employment relationship. It critically evaluates the potential interpretive tensions between Articles 4 and 5 and underscores the Directive's expansive redefinition of platform work. In doing so, the article positions the Directive as a paradigm shift in EU social regulation – one that embraces a universalistic vision of labour rights grounded in the reality of personal work rather than contractual form and employment status. The authors also reflect on the implications for future EU regulation and international standard-setting processes, particularly those led by the ILO.
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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 | 0.030 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.015 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.013 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".