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Record W1915722993 · doi:10.1017/s1474745603001393

Regulatory transparency, developing countries and the WTO

2003· article· en· W1915722993 on OpenAlexaffabout
Robert Wolfe

Bibliographic record

VenueWorld Trade Review · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicWorld Trade Organization Law
Canadian institutionsQueen's University
Fundersnot available
KeywordsTransparency (behavior)Developing countryGlobalizationBusinessCorporate governanceDemocracyIndependence (probability theory)International tradeAdaptation (eye)International economicsPublic economicsEconomicsEconomic growthPolitical scienceMarket economyLawFinancePolitics

Abstract

fetched live from OpenAlex

The tension in the WTO between adaptation to globalization and integration of developing countries is illustrated by one of the central norms of the regime, transparency. Experts believe democratic governance and efficient markets are both enhanced when autonomous administrative agencies are open about what they doing. WTO requirements for regulatory transparency may prove to be more straightforward for OECD countries than developing countries. The future of the WTO as a legitimate and effective international organization depends on finding modes of regulation accessible to all its Members. A review of how Canada, Brazil, South Africa, Thailand, and Uganda implement the transparency requirements of the agreements on basic telecommunications, and sanitary and phytosantitary measures found that regulatory independence and transparency are increasingly prevalent in telecommunications, but much less so in food safety. Transparency between countries appears easier than transparency within countries, and economic regulation seems easier to adapt to international norms than social regulation.

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)0.020
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.020
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.030
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.005
Science and technology studies0.0040.016
Scholarly communication0.0110.008
Open science0.0010.004
Research integrity0.0070.010
Insufficient payload (model declined to judge)0.0040.001

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 head0.022
GPT teacher head0.286
Teacher spread0.264 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations49
Published2003
Admission routes2
Has abstractyes

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