Competitive Strategies and Worker Outcomes in the US Retail Industry
Bibliographic record
Abstract
The retail industry is both the largest industry in the U.S. in terms of employment, and the largest employer of low‐wage workers in the U.S. Though over‐ all, women made up 49% of the retail workforce in 2007, just above the economy‐wide proportion of 47%, when we narrow our sights to part‐time, frontline retail workers (cashiers and stock clerks), the female percentage jumps to 64%, compared to only 33% in management.\n Retail salaries are low, particularly for the many part‐time workers. Frontline grocery workers—cashiers and stock clerks—earn 57 percent of the average hourly rate across all private industries. In electronics, frontline workers do a little better at 85 percent of the average wage. Not surprisingly, this is at least in part a gender story. Half of all grocery store workers are female compared with just over a quarter (28%) of electronics workers. Among full‐ time, frontline workers the gender disparity between grocery and electronics is even greater.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".