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Record W4220919753 · doi:10.26509/frbc-wp-202207

Labor Substitutability among Schooling Groups

2022· report· en· W4220919753 on OpenAlex
Mark Bils, Barış Kaymak, Kai-Jie Wu

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

VenueWorking paper · 2022
Typereport
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Productivity
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsEconomicsHuman capitalElasticity of substitutionSubsidyWageImmigrationLabour economicsFrontierQuality (philosophy)Demographic economicsProduction (economics)MicroeconomicsEconomic growthMarket economyGeography

Abstract

fetched live from OpenAlex

Knowing the degree of substitutability between schooling groups is essential to understanding the role of human capital in income differences and to assessing the economic impact of such policies as schooling subsidies, immigration systems, or redistributive taxes. We derive a lower bound for the substitutability required for worldwide growth in real GDP from 1960 to 2010 to be consistent with a stable wage premium for schooling despite the rapid growth in schooling, assuming no exogenous worldwide regress in the technology frontier for workers with only primary schooling. That lower bound for the long-run elasticity of substitution is about 4, which is far higher than values commonly used in the literature. Given our bound, we reexamine the importance of human capital in cross-country income differences and the roles of school quality versus the skill bias of technology in greater efficiency gains from schooling in richer countries.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.776
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.052
GPT teacher head0.235
Teacher spread0.182 · 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