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Record W2737514898 · doi:10.1177/0020715217719313

Boon or bane: Examining divergent development outcomes among oil- and mineral-dependent countries in the Global South

2017· article· en· W2737514898 on OpenAlexvenueno aff
Zophia Edwards

Bibliographic record

VenueInternational Journal of Comparative Sociology · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicNatural Resources and Economic Development
Canadian institutionsnot available
FundersWorld Bank Group
KeywordsResource curseDependency (UML)Developing countryEconomicsState (computer science)CurseDevelopment economicsDebtPrivilege (computing)Political scienceNatural resourceEconomic growthSociologyMacroeconomics

Abstract

fetched live from OpenAlex

Under neoliberal conditions that privilege foreign investors and call for the retreat of the state, some oil- and mineral-dependent countries in the Global South outperform others. To investigate what accounts for this variation in economic development among these countries, this study tests hypotheses derived from resource curse and dependency/world systems literatures using a dataset of 36 oil- and mineral-dependent countries in the Global South from 1984 through 2010 and panel methods of data analysis. The results show that state capacity and debt dependence shape uneven development outcomes among these countries. The implications for resource curse and dependency/world systems theories are discussed.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.097
GPT teacher head0.321
Teacher spread0.224 · 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 designObservational
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

Citations11
Published2017
Admission routes1
Has abstractyes

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