Some Think of the Future: Internet, Electronic, and Telephonic Labor Representation Elections
Bibliographic record
Abstract
Amid the scholarly dialogue regarding amending labor certification procedures, there have been calls for the adoption of Internet, electronic, and/or telephonic representation voting (“IETV”) procedures in representation elections. To date, most labor relations agencies in the United States and Canada have not implemented IETV. Three notable exceptions are the National Mediation Board (“NMB”) and the Federal Labor Relations Authority (“FLRA”) in the United States, and the Canada Industrial Relations Board (“CIRB”). This Article explores the strengths and weaknesses of IETV and the potential for wider adoption of this technology in the representation election context. The Article examines NMB’s rationale in adopting IETV, and its experience with this new election format. Insights and experiences from interview participants provide a fuller examination of the prospects and pitfalls of IETV than previous research. The primary rationale for adopting IETV has been premised on pragmatic administrative decision-making, rather than minimizing employer and union interference in voting. Findings also show that IETV has been adopted as a substitute for mail-ballot elections, and not as a replacement for manual elections. These findings have implications for extending the adoption of IETV to other labor relations agencies. This Article posits that while IETV is an important innovation in the representation electoral process, it is too early for there to be universal adoption of the format without additional research and experimentation. In experimenting with IETV, the focus should be on determining whether IETV fulfills the fundamental purpose of a representation election: to accurately reflect whether or not employees in a unit wish to be represented by the applicant union. Moreover, in introducing IETV, an agency must explore new means of communicating with unit employees aimed at maximizing participation under the new election format.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| 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".