MétaCan
Menu
Back to cohort
Record W4398168691 · doi:10.1093/jiel/jgae017

Discourses of ISDS reform: a comparison of UNCITRAL Working Group III and ICSID processes

2024· article· en· W4398168691 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of International Economic Law · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicMormonism, Religion, and History
Canadian institutionsCarleton UniversitySocial Sciences and Humanities Research CouncilMcGill UniversityUniversity of CalgaryUniversité de Montréal
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsGroup (periodic table)Political scienceLaw and economicsBusinessSociologyChemistry

Abstract

fetched live from OpenAlex

Abstract The reform of investor-state dispute settlement (ISDS) has been tackled by the International Centre for Settlement of Investment Disputes (ICSID) and United Nations Commission on International Trade Law (UNCITRAL) Working Group (WG) III. Despite different objectives, both processes have relied on written submissions from various stakeholders. What are the structures and the narratives underlying the discourses of ISDS reform in these organizations? This article explores the content of 172 submissions by using mixed methods. It demonstrates that UNCITRAL WG III has involved less structured submissions whose content has expanded the initial mandate, with narratives encapsulating deeper disagreement among participants. By contrast, ICSID operated through a common pattern across submissions and a stronger focus on procedural issues, with less disagreement revealed in its narratives. The article proceeds in three steps. First, it compares the structure of discourses for each reform process by aggregating the content of submissions through computational analysis. Second, it relies on critical discourse analysis to reveal narratives that have emerged in each process. Lastly, the article explores submissions from actors who have participated in both processes to illustrate how they have navigated the tension between structures and narratives when reforming international investment arbitration.

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.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.974
Threshold uncertainty score0.305

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 head0.030
GPT teacher head0.267
Teacher spread0.237 · 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