Workplace Gains beyond the Wagner Act: The New York Taxi Workers Alliance and Participation in Administrative Rulemaking
Bibliographic record
Abstract
Workers in traditional employment relationships have long relied on unionization and collective bargaining to counter unequal power relationships in the workplace and improve the terms and conditions of their work. Within the North American context, however, workers in select industries or with select employment status are legally excluded from this paradigm and unable to access basic labor law protections. This article examines historic gains made by the New York Taxi Workers Alliance to improve the work experience of yellow cab drivers through collective participation in the City of New York’s Administrative Rulemaking process. Exploring examples, including the 2003/2004 meter increase, Driver’s Bill of Rights, and the Drivers’ Benefit Fund, I argue that in the absence of a collective bargaining agreement, administrative rulemaking can provide both a site for negotiation about the content and structure of work, and can be employed to uphold the rights and gains made through workers’ collective action.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.015 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 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".