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Record W1555132671

Toeing the Line: Arbitrators with Expert Knowledge [Xerox Canada Ltd. v. MPI Technologies Inc]

2007· article· en· W1555132671 on OpenAlexaboutno aff
Nicholas Pengelley

Bibliographic record

VenueSSRN Electronic Journal · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Arbitration and Investment Law
Canadian institutionsnot available
Fundersnot available
KeywordsPlaintiffArbitrationLawEconomic JusticeBusinessPolitical science
DOInot available

Abstract

fetched live from OpenAlex

In Xerox Canada Ltd v. MPI Technologies Inc, Justice C.L. Campbell rejected a challenge to the ward of a three-person arbitral panel. The plaintiff, Xerox Canada, had alleged that one of the arbitrators, who had expert knowledge of some of the complex technical evidence that was at the core of the dispute, had crossed the line and acted in a non-judicial manner, contrary to the UNCITRAL Model Law on International Commercial Arbitration (the Model Law). The decision is important for its review of, and support for, the manner in which the panel both utilized the knowledge of the expert arbitrator and observed its responsibilities to the parties in so doing. It is contended that the panel's behaviour represents a model of its kind.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.503
Threshold uncertainty score1.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.021
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0230.010
Scholarly communication0.0130.008
Open science0.0020.003
Research integrity0.0200.010
Insufficient payload (model declined to judge)0.0090.001

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.

Opus teacher head0.007
GPT teacher head0.215
Teacher spread0.208 · 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 source (direct Gemma or distilled Codex), not a consensus.

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