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Record W2800397568 · doi:10.7202/1044430ar

Expedited Arbitration: A Study of Outcomes and Duration

2018· article· en· W2800397568 on OpenAlexaffvenueabout
Shannon Webb, Terry H. Wagar

Bibliographic record

VenueRelations industrielles · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicLaw, Economics, and Judicial Systems
Canadian institutionsQueen's UniversitySaint Mary's UniversityFanshawe College
Fundersnot available
KeywordsArbitrationDismissalGrievanceCompulsory arbitrationBusinessLegislationSample (material)Process (computing)LawPolitical scienceComputer science

Abstract

fetched live from OpenAlex

In both academic and practitioner communities, there is an increased concern related to the time-consuming nature of the traditional labour arbitration system in Canada. The arbitration process was initially instituted to combat the delays and costs experienced in the courts. This study addresses the gap in the scientific literature by considering these ongoing concerns. Many Canadian jurisdictions offer the parties an opportunity to expedite the arbitration process pursuant to applicable legislation. However, despite the opportunity to accelerate the process, there appears to be a reluctance to use the expedited arbitration system. We performed content analysis on over 550 Canadian expedited and traditional labour arbitration cases. The case sample was limited to termination cases. We studied and compared delay at multiple times during the arbitration process, including the delay to the hearing, delay to the arbitration award, and total delay. Furthermore, we studied the case outcome; specifically, whether the grievance was granted or denied and adopted an ordered analysis to investigate differences in case outcomes. Our results support the perception that there is a difference in the expediency of expedited arbitration cases in comparison with traditional arbitration cases. The results also show that the outcomes of dismissal cases, decided in the expedited system, do not significantly differ from the traditional arbitration system. The findings suggest that there are statutorily available opportunities for the parties to accelerate the arbitration process without compromising the results.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.092
Threshold uncertainty score0.413

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 head0.050
GPT teacher head0.243
Teacher spread0.193 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2018
Admission routes3
Has abstractyes

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