Bibliographic record
Abstract
This article summarizes findings from the research paper entitled: Work Hours Instability in Canada. Numerous studies of working hours have drawn important conclusions from cross-sectional surveys. For example, the share of individuals working long hours is quite large at any given point in time. Moreover, this appears to have increased over the past two decades, raising the call for policies designed to alleviate working hours discrepancies among workers, or reduce working time overall. However, if work hours vary substantially at the individual level over time, then conclusions based upon studies of cross-sectional data may be incomplete. Using longitudinal data from the Canadian Survey of Labour and Income Dynamics, we find that there is substantial variation in annual working hours at the individual level. In fact, as much as half of the cross-sectional inequality in annual work hours can be explained by individual-level instability in hours. Moreover, very few individuals work chronically long hours. Instability in work hours is shown to be related to low-job quality, non-standard work, low-income levels, stress and bad health. This indicates that working variable work hours is not likely done by choice; rather, it is more likely that these workers are unable to secure more stable employment. The lack of persistence in long work hours, plus the high level of individual work hours instability undermines the equity based arguments behind working time reduction policies. Furthermore, this research points out that policies designed to reduce hours instability could benefit 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.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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".