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Record W4362565517 · doi:10.5040/9781641899628

The Global North

2021· book· en· W4362565517 on OpenAlexaboutno aff

Bibliographic record

VenueBloomsbury Publishing eBooks · 2021
Typebook
Languageen
FieldSocial Sciences
TopicKorean Peninsula Historical and Political Studies
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Latin AmericansDeveloping countryGeographyDevelopment economicsPopulationPoliticsWorld populationDeveloped countryPolitical scienceEconomic growthEconomicsDemographySociology

Abstract

fetched live from OpenAlex

The concept of Global North and Global South (or North–South divide in a global context) is used to describe a grouping of countries along the lines of socio-economic and political characteristics. The Global South is a term generally used to identify countries in the regions of Latin America, Africa, Asia and Oceania. Most, though not all of the countries in the Global South are characterized by low-income, dense population, poor infrastructure, often political or cultural marginalization,[1] and are on one side of the divide; while on the other side is the Global North (comprising the United States, Canada, all European countries, Russia, Israel, Japan, South Korea, Australia, New Zealand and few others depending on context).[2][3][4] As such, the terms Global North and Global South do not refer to the directional North-south as many of the Global South countries are geographically located in the Northern Hemisphere. Countries that are developed are considered as Global North countries, while those developing are considered as Global South countries.[6][1] The term as used by governmental and developmental organizations was first introduced as a more open and value-free alternative to "Third World"[7] and similarly potentially "valuing" terms like developing countries. Countries of the Global South have been described as newly industrialized or are in the process of industrializing, and are frequently current or former subjects of colonialism.[8] The Global North generally correlates with the Western world—with the notable exceptions of Israel, Japan, and South Korea—while the South largely corresponds with the developing countries and the Eastern world. The two groups are often defined in terms of their differing levels of wealth, economic development, income inequality, democracy, and political and economic freedom, as defined by freedom indices. States that are generally seen as part of the Global North tend to be wealthier and less unequal; they are developed countries, which export technologically advanced manufactured products. Southern states are generally poorer developing countries with younger, more fragile democracies heavily dependent on primary sector exports, and they frequently share a history of past colonialism by Northern states.[8] Nevertheless, the divide between the North and the South is often challenged.[9] South-South cooperation has increased to "challenge the political and economic dominance of the North."[10][11][12] This cooperation has become a popular political and economic concept following geographical migrations of manufacturing and production activity from the North to the Global South[12] and the diplomatic action of several states, like China.[12] These contemporary economic trends have "enhanced the historical potential of economic growth and industrialization in the Global South," which has renewed targeted SSC efforts that "loosen the strictures imposed during the colonial era and transcend the boundaries of postwar political and economic geography."[13] Used in several books and American Literature special issue, the term Global South, recently became prominent for U.S. literature.[14]

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)0.001
metaresearch head score (Gemma)0.003
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.136
Threshold uncertainty score0.455

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.004
Scholarly communication0.0110.010
Open science0.0010.007
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.1360.036

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 head0.028
GPT teacher head0.269
Teacher spread0.241 · 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
GenreOther

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
Published2021
Admission routes1
Has abstractyes

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