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Record W3022811721 · doi:10.1111/iere.12022

THE EVOLUTION OF EDUCATION: A MACROECONOMIC ANALYSIS

2013· article· en· W3022811721 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

VenueInternational Economic Review · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Productivity
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEducational attainmentHuman capitalEconomicsLife expectancyDistribution (mathematics)Demographic economicsTechnological changePopulationExpectancy theoryEconometricsEconomic growthMacroeconomicsDemographySociology

Abstract

fetched live from OpenAlex

Between 1940 and 2000 there was a substantial increase in educational attainment in the United States. What caused this trend? We develop a model of human capital accumulation that features a nondegenerate distribution of educational attainment in the population. We use this framework to assess the quantitative contribution of technological progress and changes in life expectancy in explaining the evolution of educational attainment. The model implies an increase in average years of schooling of 24%, which is the increase observed in the data. We find that technological variables and in particular skill‐biased technical change represent the most important factors in accounting for the increase in educational attainment. The strong response of schooling to changes in income is informative about the potential role of educational policy and the impact of other trends affecting lifetime income.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.806
Threshold uncertainty score0.996

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.005

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 head0.018
GPT teacher head0.250
Teacher spread0.232 · 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