Overtime Activists Take on Corporate Titans: Toyota, Mc Donald's and Japan's Work Hour Controversy
Bibliographic record
Abstract
Japan’s long work hours generate high human and economic costs. Even between 2002 and 2008, when Japan enjoyed a growing economy, the media regularly reported cases of workers felled by strokes and heart attacks or driven to depression or suicide by unrelenting job demands. Work hours are a major impediment to equal opportunity, since working mothers cannot devote the long hours expected of professional employees and so must opt for low-paying, low-status jobs. Family life is affected because many younger persons postpone or abandon hopes of marriage and children as they sacrifi ce personal lives to stay employed. Further, while long work hours and karō (overwork) are common in many countries, notably the US and Britain, in Japan karōshi (death from overwork) has been offi cially recognized as a medico-legal phenomenon for two decades, and has spawned a social movement to combat it.1 Japan’s employers and conservative policymakers have long held that the country’s pattern of incremental and consensual policy making is effective in improving employment conditions, while avoiding the economic rigidities of Western nations. The result since the 1950s has been labour legislation that consistently lags behind labour market trends, or seeks merely to defuse complaints from trade partners that poor labour standards constitute unfair trade practices.2 Work-hour-related policy making closely matches this pattern: long work hours have provoked consistent attempts at reform since the late 1960s, and reformers made several signifi cant revisions to labour laws between 1987 and 1993, but failed to signifi cantly affect actual practice. While many large manufacturing fi rms did reduce work hours around this
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.013 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.020 | 0.017 |
| Insufficient payload (model declined to judge) | 0.011 | 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".