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Record W4381186032 · doi:10.1093/arbint/aiad033

William W. (Rusty) Park, General Editor, <i>Arbitration International</i> 2006–2022

2023· article· en· W4381186032 on OpenAlexaffabout
Andrea K. Bjorklund

Bibliographic record

VenueArbitration International · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Arbitration and Investment Law
Canadian institutionsMontreal General Hospital
Fundersnot available
KeywordsArbitrationInternational arbitrationLawPolitical scienceLibrary scienceSociologyComputer science

Abstract

fetched live from OpenAlex

Just under a year ago, William W. (Rusty) Park asked Ruth Teitelbaum and me to succeed him as co-general editors of Arbitration International. We were pleased and honoured to accept, even as we recognized the challenges inherent in succeeding someone who had led the journal so ably for the past 17 years. One of our first thoughts was how to mark Rusty’s contributions to this journal and by extension to the entire arbitration community, which relies on and relishes the articles found in the distinctive orange-coloured volumes that grace the shelves of so many libraries and arbitration specialists. Because Arbitration International flourished under Rusty’s stewardship, we decided a perfect tribute to him would be to publish a special edition of contributions written by his many friends, admirers, and co-arbitrators—indeed, in many instances, the authors below would place themselves in all three categories. John Townsend, Rusty’s friend since they were together at Yale College, agreed immediately to co-lead the endeavour. In the hope of creating a volume that could be presented to Rusty at Tylney Hall in September 2023, we gave the invited authors a rather strict deadline—something a bit unusual in the publishing world, but essential if we were going to be able to present the volume to him at that event, so fitting given the connection between the London Court of International Arbitration and Arbitration International. Notwithstanding their many other commitments, nearly everyone we invited said yes with alacrity and even enthusiasm. We offered the authors great freedom to choose their preferred offering, and they embraced that flexibility by presenting a wide variety of contributions. The pieces that follow range from personal reminiscences to full-fledged scholarly masterpieces, with many offerings including both the personal and the professional, the witty and the wise; all fitting tributes to someone whose fund of perfect stories—usually humorous; always à propos—seems never to be exhausted.

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)0.002
metaresearch head score (Gemma)0.009
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.052
Threshold uncertainty score0.174

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0060.003
Open science0.0010.001
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0520.049

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 head0.014
GPT teacher head0.242
Teacher spread0.228 · 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
GenreEditorial

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
Published2023
Admission routes2
Has abstractyes

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