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Record W7097589950

Short Hours, Long Hours: Hour Levels and Trends in the Retail Industry in the United States, Canada,

2012· article· en· W7097589950 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Retail Behavior Studies
Canadian institutionsnot available
Fundersnot available
KeywordsJob lossRetail industryQuality (philosophy)Argument (complex analysis)Retail tradeEstimation
DOInot available

Abstract

fetched live from OpenAlex

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. Results broadly support our predictions, especially the distinction between the United States and Canada

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.262
Threshold uncertainty score0.528

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.077
GPT teacher head0.275
Teacher spread0.199 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

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