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Record W4404562553 · doi:10.1093/isagsq/ksae080

The North–South Distinction: From Consensus to Contestation

2024· article· en· W4404562553 on OpenAlexafffund
Jean‐Philippe Thérien

Bibliographic record

VenueGlobal Studies Quarterly · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicPublic health and occupational medicine
Canadian institutionsUniversité de Montréal
FundersUniversity of CambridgeUnited Nations Development ProgrammePrinceton UniversityUniversity of OxfordHarvard UniversitySocial Sciences and Humanities Research Council of CanadaWorld Bank Group
KeywordsWashington ConsensusPolitical scienceConsensus conferenceComputer scienceLawLibrary sciencePolitics

Abstract

fetched live from OpenAlex

Abstract Rooted in the field of intellectual history, this article examines how the meaning of the North–South distinction has changed since its appearance in the 1960s. It explains how the largely consensual vision espoused during the early years has gradually given way to growing polarization and contestation. This evolution is unpacked by studying the genealogy of North–South narratives formulated through the ideologies of liberal internationalism and systemic reformism. The article shows that the 1960–1990 period brought about an international compromise regarding the existence of a North–South divide. Moving to the post-1990 period, the analysis then dissects the growing disagreements over the utility of the North–South terminology for interpreting the global order. While today moderate and radical reformists continue to argue that the North–South cleavage remains a structural feature of global politics, most liberals maintain that it simply fails to describe the real world. Overall, the article helps to clarify what makes the North–South distinction highly contested and nonetheless “sticky” in contemporary global affairs.

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)0.023
metaresearch head score (Gemma)0.023
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 score0.023
Threshold uncertainty score0.122

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0090.090
Scholarly communication0.0150.015
Open science0.0020.013
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0040.000

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 head0.047
GPT teacher head0.400
Teacher spread0.353 · 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

Citations8
Published2024
Admission routes2
Has abstractyes

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Same venueGlobal Studies QuarterlySame topicPublic health and occupational medicineFrench-language works237,207