It’s the End of Working Time as We Know It: New Challenges to the Concept of Working\n Time in the Digital Reality
Bibliographic record
Abstract
This article strives to unpack the concept of labour time in the digital reality. It does so by exploring the apparent gap between de jure notions of work and rest times, especially in Canada, and the way that people conduct their work time de facto given the technological advancements that enable them to work from a distance.These recent challenges to the notion of working time have led to two main proposals of regulation. The first aims to return to the classical concept of working time and to restrict the working schedule. The other aims to celebrate the new technological capabilities to conduct work anytime and anyplace and disregards the dominant role of time in labour law. This article argues that these opposing models provide only partial solutions and both suffer from crucial deficiencies: they either ignore the dramatic changes in the world introduced by digital technology, or worse, they ignore the basic idea and purposes of labour rights.Based on this struggle between labour law and technology, this article suggests a new paradigm for working time regulation—one which brings together the logic and structure of the new flexible online world with the basic principles of labour rights. This article thereby proposes default rules that provide basic protection to the employee and retain the idea that employees should be compensated for their actual working time and enjoy genuine rest time during the workday. This protection is enabled through the format and logic of information communication technology. At the same time, this article suggests that the default rules will also enable the parties to negotiate and agree on the financial value of additional working hours, in a way that takes into account the new possibilities of the digital age along with the purposes of labour rights.
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.
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 | 0.000 | 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 | 0.000 |
| 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 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".