Hour Levels and Trends in the Retail Industry
Bibliographic record
Abstract
In settings where most workers have full-time schedules, hourly wages are appropriate primary indicators of job quality and worker outcomes. However, in sectors where full-time schedules do not dominate— primarily service-producing activities—total hours matter, in addition to hourly wages, for job quality and worker outcomes. In this paper we employ a sector-focused, comparative framework to further examine hours levels—measured as average weekly hours—and trends in Canada, the United States, and Mexico. We analyze the retail sector, which is of interest because of its high rate of part-time employment in the U.S. Based on our fieldwork in the United States and Mexico and qualitative literature on Canadian retail work, we argue that the combination of business strategies and very different institutional constraints will lead U.S. retailers to a greater extent and Canadian retailers to a lesser extent to shorten hours and expand part-time jobs, whereas in Mexico it will lead retailers to lengthen hours. We apply this argument to predictions about differences in levels and trends. Drawing on standard public data sources from the three countries, we compare means and run time series regressions to estimate trends net of cyclical effects.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".