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Record W4400606534 · doi:10.54648/amdm2020032

Editorial

2020· editorial· en· W4400606534 on OpenAlexaboutno aff
Stavros Brekoulakis

Bibliographic record

VenueArbitration. · 2020
Typeeditorial
Languageen
FieldArts and Humanities
TopicArtistic and Creative Research
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

It is a rare moment in the professional life of a Journal Editor when everything seems to fall into place.In the case of this Journal Editor, this means that the selected submissions for the current issue deal with a range of diverse dispute resolution topics.Specifically, the issue includes articles on international commercial arbitration, for example Srishti Kumar's comparative analysis of transparency and confidentiality; articles on investment treaty arbitration, for example Felisa Baena's review of recent ICSID awards on valuation of 'non-operational projects'; articles on construction arbitration, for example Bwalya Lumbwe's investigation of the claims and dispute referral procedures under the latest FIDIC 2017 Edition of Contracts; and articles on conflicts of laws, for example Michael Kern's analysis of the relevance of Rome I Regulation for international arbitration.Further, the issue includes not only topics of practical importance, for example the proposal put forward by Lal, Casey, Kaiding and Defranchi on the appropriate remedies against abuse of document production, and Peter Ashford's review of arbitrators' powers to disqualify counsel and experts; but also analytical articles dealing with complex concepts, for example Janet Walker's review of the recent decision of the Supreme Court of Canada in Heller v Uber examining issues of procedural arbitrability, and Bankole Sodipo's discussion of non-disclosure and allegations of bias.The issue finally includes James Clanchy's interesting conference paper defending the importance of ad hoc arbitration.It has been a key editorial goal for this Journal to expand its scope and publish articles of international interest that address both theoretical and practical issues from a wide range of dispute resolution sub-fields.While the Journal is also keen to include submissions from other fields of dispute resolution, chiefly on mediation, this issue brings us closer to achieving our goal.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.373
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.025
GPT teacher head0.279
Teacher spread0.254 · 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; both teacher heads agree on what is shown here.

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
Published2020
Admission routes1
Has abstractyes

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