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Record W3186636713 · doi:10.1093/chinesejil/jmab012

The Emergence of Objective Guidelines for Granting Immunity to International Non-Governmental Organizations

2021· article· en· W3186636713 on OpenAlexaff
David Pavot, Lolita Laperle-Forget

Bibliographic record

VenueChinese Journal of International Law · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Security and Public Health
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsPolitical scienceJurisdictionMultilateralismAllianceInternational lawPromulgationLawState (computer science)Public administrationTreatyPolitics

Abstract

fetched live from OpenAlex

Abstract Out of thousands of international non-governmental organizations (INGOs), only five benefit from immunities from jurisdiction and execution: the International Committee of the Red Cross (ICRC), the International Union for Conservation of Nature (IUCN), the Global Fund to Fight AIDS, Tuberculosis, and Malaria; Gavi, the Vaccine Alliance (Gavi), and the World Anti-Doping Agency (WADA). Based on empirical research, this article argues that there is an emerging State practice in granting immunity only to INGOs that meet two cumulative criteria: a hybridity character and a mission of international interest, formally recognized in a source of international law. This article proposes a new approach based on both Functionalism and Institutionalism that addresses the specificities of INGOs and thus shows that international law provides guidance on the granting of immunities.

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)0.001
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
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 score0.911
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.024
GPT teacher head0.393
Teacher spread0.369 · 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.

Study designTheoretical or conceptual
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
Published2021
Admission routes1
Has abstractyes

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