Employee Free Choice: Amplifying Employee Voice without Silencing Employers - A Proposal for Reforming the National Labor Relations Act
Bibliographic record
Abstract
This Note investigates the effectiveness of the National Labor Relations Act (NLRA) in balancing unions, employers', and employees' rights during the course of union organizing drives. After reviewing case law and commentary, it concludes that the NLRA's certification regime is ineffective and permits pressures that inhibit employees from expressing their real desires about whether or not to be represented by a union. This Note then examines proposed alternatives for certifying unions, and takes note of Canada's federal and ten provincial certification regimes. Finally, it concludes that the NLRA must be amended to protect worker free choice, and proposes reforms including limiting unions to a public sixty-day organizing campaign, designing a uniform authorization card to be submitted with a fee by employees desiring union representation, and establishing a verification process for these cards.
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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 | 0.039 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.029 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.033 | 0.015 |
| Insufficient payload (model declined to judge) | 0.003 | 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".