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Record W4409339311 · doi:10.1017/s1053837225000057

TEACHING GENERAL EQUILIBRIUM THEORY IN THE EARLY TWENTIETH CENTURY: AN ANALYSIS OF TREATISES

2025· article· en· W4409339311 on OpenAlexaff
Lúcia Regina Centurião

Bibliographic record

VenueJournal of the History of Economic Thought · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Theory and Institutions
Canadian institutionsUniversity of Regina
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsEconomicsMathematical economicsNeoclassical economicsPhilosophyKeynesian economicsHistoryEpistemologyPositive economics

Abstract

fetched live from OpenAlex

This paper investigates the teaching of Walrasian general equilibrium theory in the early twentieth century through an analysis of three treatises: Arthur Bowley’s The Mathematical Groundwork of Economics (1924), Gustav Cassel’s The Theory of Social Economy (1924), and Étienne Antonelli’s Principes d’économie pure (1914). Despite their original contributions, the three works were also intended to be read by students. Examining these treatises contributes to a historical understanding of pre-war economics education literature and sheds light on the evolution of mathematical economics, particularly within the context of the educational process. The paper concludes that while all three treatises presented Léon Walras’s general equilibrium framework, they simultaneously reflected diverse fundamental beliefs about economic science, such as its objective and scope. Notably, there was no singular dominant group appropriating Walras’s model. However, a content analysis revealed structural similarities among the treatises.

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)0.005
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.995
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0070.008
Science and technology studies0.0050.013
Scholarly communication0.0060.004
Open science0.0010.003
Research integrity0.0020.004
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 head0.024
GPT teacher head0.242
Teacher spread0.218 · 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.

Study designQualitative
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
Published2025
Admission routes1
Has abstractyes

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