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Record W4406271787 · doi:10.56238/sevened2024.037-151

PERIPHERAL’STATE RESPONSIBILITY UNDER GLOBALIZATION VS SOCIAL EXCLUSION AND SUSTAINABILITY: A CHALLENGE FOR MEXICO AND LATIN AMERICA IN CURRENT CENTURY

2025· book-chapter· en· W4406271787 on OpenAlexaboutno aff
Octavio Luis-Pineda

Bibliographic record

VenueSeven Editora eBooks · 2025
Typebook-chapter
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsnot available
Fundersnot available
KeywordsLatin AmericansSustainabilityState (computer science)GlobalizationPolitical scienceCurrent (fluid)Development economicsEconomicsEngineeringLawComputer scienceBiologyEcology

Abstract

fetched live from OpenAlex

The majority of peripheral (and emerging) economies such as Mexico and other countries in Latin America and some other in peripheral regions around the world have undergone during the last four decades, socioeconomic, political, and environmental woes triggered not only by recurrent international financial crises in world markets, but also stemming from their long-time structural social, economic, and political problems such as unemployment, poverty, malnutrition, margination, income maldistribution, corruption and some unexpected temporary phenomenon such as the pandemic, which have entailed and inflicted a huge unprecedented social and economic costs both to peripheral but also developed economies, along to a host of externalities, producing social and environmental costs vis-a-vis the advent of globalization and trade liberalization and the concomitant increase of international trade between Mexico and the rest of the world, particularly between Mexico and its trade partners, under UMSCA treaty, namely, United States, and Canada. Under this context, it is worth mentioning the lack of a long-term strategy from most peripheral economies to not overlooking their States’ responsibility to promote long-term strategies aiming at curtailing the historically unbalanced growth pattern they have observed through time such as growing unemployment, income maldistribution, and notoriously, unsustainable handling of their natural resources along with other externalities. This article aims to highlight the fact that under today's current global context, it comes out manifest a clear lack of long-term commitment from their States to implement strategies aiming to balance the binomial economic growth well-being under a sustainable framework in most peripheral economies, among manifold factors and particularly the pervasive presence and influence of international hegemonic institutions such as the World Bank, IMF in major economies, in Latin America and elsewhere throughout the periphery which has undermined the efforts of democratic governments to shift the current neoliberal-oriented-policies to maximize profit-at-all-cost strategies which have undermined population’s social wellbeing and sustainability prevailing throughout the periphery by another alternative one, a more socially inclusive and sustainably oriented strategy. One committed to paralleling fostering, economic growth and the people’s well-being in a country. Such a model currently prevails in some advanced socially inclusive economies (Scandinavian countries, Switzerland, Canada, etc.), versus the situation faced by the majority of peripheral economies, as in Latin America, including Mexico, during the last decades. The bottom line of this article is to disclose some underlying factors and circumstances that have prevented a reorientation of the prevailing neoliberal strategies in peripheral economies, namely, those socioeconomic factors and political circumstances under which an emerging economy such as Mexico is currently successfully implementing a socially inclusive and sustainable strategy far from the so-called Washington Consensus, vid, Hurt, Stephen R.(May 27, 2020).

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)0.003
metaresearch head score (Gemma)0.002
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 score0.027
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.009
Scholarly communication0.0080.005
Open science0.0010.006
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0050.000

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 head0.017
GPT teacher head0.312
Teacher spread0.295 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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