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Record W2576562172

Desarrollo Humano y los desafíos de la Global Governance: Por una rediscusión de la clasificación de los Middle Powers

2016· article· es· W2576562172 on OpenAlexaboutno aff
Ernani Contipelli

Bibliographic record

VenueCuestiones Políticas · 2016
Typearticle
Languagees
FieldSocial Sciences
TopicInternational Relations in Latin America
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesMiddle powerPhilosophyPoliticsForeign policyLaw
DOInot available

Abstract

fetched live from OpenAlex

En el contexto de los asuntos internacionales, dos grupos de paises reciben una particular atencion de los analisis academicos y politicos: Traditional Middle Powers y Emerging Middle Powers. Traditional Middle Powers son representados por paises industrializados, democraticos e igualitarios con un alto nivel de desarrollo social y politico y considerados como good international citizens, por auxiliar en el sostenimiento del orden implantado por las potencias hegemonicas(como ejemplo, Australia, Canada, Japon). El concepto de Emerging Middle Powers respecta a paises con gran performance economico y proyeccion internacional, pero despreocupados con politicas de bienestar, especialmente, porque no presentan un sistema politico democratico consolidado y un adecuado nivel de igualdad social, como el caso de los BRICS (Brasil, Rusia, India, China y Sudafrica). En ese complejo escenario, es posible encontrar un grupo de paises que, desapercibido por la teoria politica internacional, situase en un punto intermedio entre las Traditional y Emerging Middle Powers. Ellos son caracterizados por la existencia de politicas orientadas a la conjugacion de crecimiento economico y oferta de buena calidad de vida a la poblacion, lo que refleja en sus altos niveles de Desarrollo Humano (IDH). Asi, constatamos la necesidad de construir una identidad conceptual para ese grupo de paises atribuyendoles un perfil politico-institucional ante el nuevo orden mundial y estableciendo su papel en el contexto internacional.

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)0.002
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.601
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.015
GPT teacher head0.374
Teacher spread0.358 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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