Algorithmic management of platform workers: An examination of the Canadian and European approaches to regulation
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
Algorithmic management, though less attention-grabbing than total job automation, is expected to become even more influential and powerful over time. The realities of algorithmic management have gained increasing scholarly attention over the last decade, particularly in the context of employment relationships in the platform economy. This article contributes to existing scholarship by comparing two important pieces of legislation impacting algorithmic management in the platform economy: Ontario's Digital Workers’ Rights Act 2022 (‘the Act’) and the Proposal for a Directive of the European Parliament and of the Council on Improving Conditions in Platform Work (‘the Directive’). The thrust of this article is that while the general tenor of the Act indicates a step in the right direction, its restrictive approach to information rights limits its overall effectiveness in regulating algorithmic management of platform workers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it