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Record W2043975160 · doi:10.1017/s0022381608080754

The Perils of Unearned Income

2008· article· en· W2043975160 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of Politics · 2008
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicNatural Resources and Economic Development
Canadian institutionsYork University
Fundersnot available
KeywordsIncentiveEconomic rentPublic goodPoliticsEconomicsNatural resourceResource cursePublic economicsMarket economyPolitical economyPolitical scienceLawMicroeconomics

Abstract

fetched live from OpenAlex

In addition to the internal risk of deposition, which is modeled using selectorate politics (Bueno de Mesquita et al.2003), leaders risk being deposed by mass political movements such as revolutions. Leaders reward supporters with either public goods, which reward the whole of society, improve economic productivity, and increase the ability of revolutionaries to organize, or private goods. If confronted with a revolutionary threat then leaders respond by either suppressing public goods—which prevents revolutionaries organizing—or increasing public goods, so citizens have less incentive to rebel. Unearned resources, such as natural resource rents or aid, increase the likelihood of revolutionary onset and effect how leaders best respond to the threat. The results address the resource curse, the potentially pernicious effects of foreign aid and incentives to democratize.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.678
Threshold uncertainty score0.159

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.033
GPT teacher head0.215
Teacher spread0.181 · 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