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Record W2944004197 · doi:10.1080/21622671.2019.1608851

The fiscal politics of resource revenue: federalism, oil ownership and territorial conflict in Brazil and Canada

2019· article· en· W2944004197 on OpenAlexaffabout
Daniel Béland, Catarina Ianni Segatto, André Lecours

Bibliographic record

VenueTerritory Politics Governance · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicNatural Resources and Economic Development
Canadian institutionsUniversity of OttawaUniversity of ReginaMcGill University
FundersAustralian Government
KeywordsRevenueNatural resourceFiscal federalismFederalismEconomicsPoliticsGovernment (linguistics)Argument (complex analysis)Government revenueCompetition (biology)Distribution (mathematics)Economic policyResource (disambiguation)BusinessMarket economyDecentralizationPolitical scienceFinanceLaw

Abstract

fetched live from OpenAlex

This paper explores the fiscal politics of oil revenue in Brazil and Canada, two oil-rich federal countries that have different constitutional arrangements for revenue allocation and where constituent unit governments have different powers in the energy sector. More specifically, it offers a comparative analysis of the intergovernmental relations around oil revenue distribution in both countries over the last 30 years. The argument is that constitutional provisions on natural resources in federations (federal ownership or constituent unit ownership) produce distinct federal dynamics as it pertains to intergovernmental relations. Federal government ownership of natural resources produces conflicts between constituent units as they vie for their share of the proceeds. In contrast, provincial ownership eliminates the direct competition between constituent units for natural resource revenues. Nevertheless, intergovernmental tensions over natural resources can still appear as constituent units pressure the federal government to adopt horizontal fiscal equalization formulas friendly to their oil-producing, or non-oil-producing economies.

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)0.005
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 score0.933
Threshold uncertainty score0.484

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.004
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.012
GPT teacher head0.196
Teacher spread0.184 · 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

Citations7
Published2019
Admission routes2
Has abstractyes

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