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Record W2002320753 · doi:10.1111/1467-937x.00125

Enterprise, Inequality and Economic Development

2000· article· en· W2002320753 on OpenAlexaff
Huw Lloyd‐Ellis, Dan Bernhardt

Bibliographic record

VenueThe Review of Economic Studies · 2000
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic theories and models
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEconomicsInequalityKuznets curveDistribution (mathematics)Income distributionWealth distributionEconomic inequalityProcess (computing)General equilibrium theoryDistribution of wealthMacroeconomicsEconometricsMicroeconomicsMathematics

Abstract

fetched live from OpenAlex

We characterize an equilibrium development process driven by the interaction of the distribution of wealth with credit constraints and the distribution of entrepreneurial skills. When efficient entrepreneurs are relatively abundant, a “traditional” development process emerges in which the evolution of macroeconomic variables accord with empirical regularities and income inequality traces out a Kuznets curve. If, instead, efficient entrepreneurs are relatively scarce, the model generates long-run “distributional cycles” driven by the endogenous interaction between credit constraints, entrepreneurial efficiency and equilibrium wages.

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)0.000
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.065
GPT teacher head0.290
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 designTheoretical or conceptual
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

Citations254
Published2000
Admission routes1
Has abstractyes

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