MétaCan
Menu
Back to cohort
Record W2622654590 · doi:10.1177/0020715217714298

Cycles of resource nationalism: Hegemonic struggle and the incorporation of Bolivia and Indonesia

2017· article· en· W2622654590 on OpenAlexvenueno aff
Brent Z. Kaup, Paul K. Gellert

Bibliographic record

VenueInternational Journal of Comparative Sociology · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsnot available
Fundersnot available
KeywordsNationalismResource (disambiguation)HegemonyPolitical economyDisadvantagedState (computer science)Power (physics)Economic systemDevelopment economicsSociologyPolitical scienceEconomicsEconomyEconomic growthPoliticsLaw

Abstract

fetched live from OpenAlex

Scholars often see resource nationalism as either a strategy to protect national interests or an opportunistic tactic to take advantage of capitalist market upswings. However, resource nationalism is not solely a strategy for an oppressed or disadvantaged group to gain power or glean a greater share of a nation’s resource wealth. Examining the extractive peripheries of Bolivia and Indonesia at two distinct temporal junctures, we demonstrate how global power struggles affect both the possibilities for resource nationalism and the variegated forms it takes across time. Taking resource nationalism to be an action by state actors in extractive peripheries to gain both economically and politically and linking sites and moments of resource nationalism to world-systemic processes, we argue that resource nationalism is a cyclical process shaped by the strategies of hegemons and their challengers. In addition, we argue that resource nationalism tends to garner greater benefits for actors in extractive peripheries when ascending global powers provide them viable alternative markets for their raw materials.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.015
Scholarly communication0.0090.006
Open science0.0010.008
Research integrity0.0010.002
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 head0.044
GPT teacher head0.376
Teacher spread0.331 · 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

Citations50
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Comparative SociologySame topicInternational Development and AidFrench-language works237,207