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Record W3034438072 · doi:10.1163/17087384-12340051

Dispute Settlement Mechanisms in African Regional Economic Communities: Lessons and New Developments

2020· article· en· W3034438072 on OpenAlexvenueno aff
Obert Bore

Bibliographic record

VenueAfrican Journal of Legal Studies · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicWorld Trade Organization Law
Canadian institutionsnot available
Fundersnot available
KeywordsSettlement (finance)International tradeEconomic integrationRegional integrationPolitical scienceInternational trade lawInternational free trade agreementFree tradeWorld tradePredictabilityLawEconomics

Abstract

fetched live from OpenAlex

Abstract African regional trade agreements often provide for dispute settlement mechanisms and procedures that should be followed. They also establish judicial bodies or tribunals for the respective African Regional Economic Communities. Despite the existence of judicial bodies, African governments do not usually litigate against each other on trade-related disputes. However, the few cases adjudicated by the regional judicial bodies are insightful of how contemporary trade disputes shape the development of community law. With reference to case law, this article presents lessons from regional judicial bodies. Notwithstanding the lessons learnt, there are challenges too. In response to the challenges, new developments on the continent, adopted through the African Continental Free Trade Area signal a move towards respecting rules-based trade through ensuring legal predictability and certainty for trade dispute settlement. Thus, this article will also provide a detailed analysis of the dispute settlement mechanism under the African Continental Free Trade Area, a system akin to World Trade Organisation.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.895
Threshold uncertainty score0.416

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 head0.113
GPT teacher head0.330
Teacher spread0.218 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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

Citations7
Published2020
Admission routes1
Has abstractyes

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