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Record W3159260022 · doi:10.1111/1758-5899.12922

Informal Learning and WTO Renewal: Using Thematic Sessions to Create More Opportunities for Dialogue

2021· article· en· W3159260022 on OpenAlex
Robert Wolfe

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.

Bibliographic record

VenueGlobal Policy · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicWorld Trade Organization Law
Canadian institutionsQueen's University
Fundersnot available
KeywordsDynamismSession (web analytics)Transparency (behavior)Public relationsPolitical scienceThematic mapThematic analysisMainstreamAccountabilityPublic administrationSociologyBusinessQualitative researchLawSocial scienceGeography

Abstract

fetched live from OpenAlex

Abstract ‘Thematic sessions’ bring dynamism to WTO by allowing committees to consider what works well under an agreement, including sharing experiences with implementation, what is not working, and what is next on the agenda. Thematic sessions are a broad class of meetings that are sponsored by or associated with a WTO body in some way, but that are not part of its formal meetings. The WTO held over 100 such sessions in the three years from 2017 to 2019. We found variation in how meetings are organized, which is related to the type of session, and we found variation in how themes are chosen, participation (who speaks), the degree of transparency, and funding. Comprehensive improvement is needed: some committees never hold thematic sessions, participation by capital‐based officials from developing countries is uneven, and too few sessions have a forward‐looking agenda. Enhanced use of thematic sessions can contribute to strengthening the pipeline between Geneva and capitals, and to better understanding in Geneva of what is happening on the ground.

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)0.001
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 score0.946
Threshold uncertainty score0.508

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.084
GPT teacher head0.389
Teacher spread0.305 · 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