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Record W2245999681

Innovation, Diffusion and the Distribution of Income in a Malthusian Economy

2008· preprint· en· W2245999681 on OpenAlexaff
Mark Staley

Bibliographic record

VenueRePEc: Research Papers in Economics · 2008
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Productivity
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsProductivityEconomicsDistribution (mathematics)PopulationDiffusionIncome distributionProduction (economics)Population growthGrowth rateDemographic economicsEconometricsEconomic growthMathematicsInequalityMicroeconomicsDemographyPhysicsThermodynamics
DOInot available

Abstract

fetched live from OpenAlex

Between 5000 BCE and 1800, the population of the world grew 120-fold despite constraints on the total amount of land available for production. This paper develops a model linking population growth to increasing productivity driven by random innovation and diffusion. People are endowed with a set of skills obtained from their parents or neighbours, but those skills are imperfectly applied during their lifetimes. The resulting variation in productivity leads to a distribution of income and to a process of diffusion whereby high-income activities spread at the expense of low-income activities. An analytic formula is derived for the steady-state distribution of income. The model predicts that the rate of growth of population approaches an asymptotic limit, whereupon there are no scale effects. The model also predicts that if the rate of diffusion of knowledge is increased, the growth rate will increase.

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)0.008
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 score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.003
Open science0.0010.001
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 head0.032
GPT teacher head0.268
Teacher spread0.235 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

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