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Record W4404724658 · doi:10.1163/22119000-12340343

Dispute Resolution in the AfCFTA Investment Protocol: a Preliminary Assessment and Proposal for Business and Human Rights Arbitration

2024· article· en· W4404724658 on OpenAlexaff
Akinwumi Ogunranti

Bibliographic record

VenueThe Journal of World Investment & Trade · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Arbitration and Investment Law
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsArbitrationHuman rightsInvestment arbitrationDispute resolutionBusinessProtocol (science)Investment (military)Resolution (logic)Alternative dispute resolutionLaw and economicsAccountingLawInternational investmentPolitical scienceEconomicsComputer scienceMedicineForeign direct investmentArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract This paper examines whether the Investment Protocol to the African Continental Free Trade Area (AfCFTA) Agreement aligns with international human rights law’s (IHRL) standards on the right to equality, non-discrimination, and access to an effective remedy. It argues that the Protocol’s dispute resolution model, which tilts towards ISDS, is incompatible with IHRL. This paper recommends incorporating the Hague Rules on Business and Human Rights Arbitration (Hague Rules) into the Protocol to create an IHRL-compatible dispute system, especially regarding enforcing human rights, environment, and climate obligations against investors and states. As African countries finalize the annex to the Protocol, they must replace ISDS with a BHR Arbitration framework as the dispute settlement regime within which investment players must enforce their rights.

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)0.153
metaresearch head score (Gemma)0.148
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.153
Threshold uncertainty score0.810

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1530.148
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0040.003
Science and technology studies0.0090.021
Scholarly communication0.0250.027
Open science0.0080.011
Research integrity0.0230.015
Insufficient payload (model declined to judge)0.0120.001

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 head0.026
GPT teacher head0.298
Teacher spread0.272 · 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 designNot applicable
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

Citations1
Published2024
Admission routes1
Has abstractyes

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