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Record W7036564854

Card-checks and Neutrality Agreements: How Hotel Unions Staged a Comeback in 2006

2007· article· en· W7036564854 on OpenAlexaboutno aff

Bibliographic record

VenueCornell Peter and Stephanie Nolan School of Hotel Administration (Cornell University) · 2007
Typearticle
Languageen
FieldArts and Humanities
TopicKarl Barth and Christian Theology
Canadian institutionsnot available
Fundersnot available
KeywordsNegotiationNeutralityMandateCommissionLabor relationsField (mathematics)ReferendumQuarter (Canadian coin)Set (abstract data type)
DOInot available

Abstract

fetched live from OpenAlex

Summer 2006 saw multiple negotiations between the big-city hotel operators and UNITE HERE, the union that represents hotel employees. The negotiations represented the culmination of the union's carefully set strategy to reconfigure the playing field in hotel labor relations. By arranging to have several cities' contracts expire within weeks of each other in summer 2006 and then splitting off one chain from another, the union was able to achieve its goal of selling labor peace through the threat of labor unrest. Operators in San Francisco tested the union's resolve in 2004, and the result then was a season of strikes and lockouts. Rather than endure the same scenario, operators in several other large cities negotiated for, and achieved, labor peace. While neither side is confirming the presence of neutrality and card-check agreements as part of the settlement, one of the union's stated goals was to be able to organize through the card-checks, rather than conduct secret-ballot elections. Under a card-check agreement, an employer agrees to recognize the union as its employees' representative after a majority of employees have signed cards stating that they are interested in organizing. The agreement eliminates what has traditionally been the next step, which is a secret-ballot election. Negotiations are not the only means by which unions are seeking to achieve this card-check procedure. The U.S. House of Representatives in early 2007 passed a bill that would mandate card-checks in all union campaigns. While the outlook for this bill is dim under the current administration, its fate may be determined in the 2008 election.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.036
GPT teacher head0.201
Teacher spread0.166 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2007
Admission routes1
Has abstractyes

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