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Record W2904374831 · doi:10.1017/s1053837217000670

<i>MATHEMATICS IS THE LANTERN</i>: VITO VOLTERRA, LÉON WALRAS, AND IRVING FISHER ON THE MATHEMATIZATION OF ECONOMICS

2018· article· en· W2904374831 on OpenAlexaff
Sonya Marie Scott

Bibliographic record

VenueJournal of the History of Economic Thought · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Theory and Institutions
Canadian institutionsYork University
Fundersnot available
KeywordsAbstractionField (mathematics)Work (physics)Positive economicsSociologyMathematical economicsEconomicsNeoclassical economicsSocial scienceEpistemologyMathematicsPhilosophyPhysics

Abstract

fetched live from OpenAlex

The interdisciplinary project to unite the field of mathematics with the social and biological sciences marks the work of Vito Volterra, one of Italy’s most prominent mathematicians of the twentieth century. This paper explores the connections between Volterra’s 1901 inaugural address at the Accademia dei Lincei in Rome and the work of two of his contemporaries, Léon Walras and Irving Fisher. All three thinkers were ardent advocates of the mathematical turn in economic thinking. This paper argues, however, that it is the previously unexplored relationship between Volterra and Fisher that sheds the most light on the way in which mechanical physics contributed to the project of mathematization within economics more generally. Furthermore, it explores the way in which mathematical inquiry postulated a new and coherent abstraction of the economy, at the same time that it gave epistemological authority to the economist.

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)0.005
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.998
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.008
Scholarly communication0.0050.006
Open science0.0000.001
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0030.001

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 head0.040
GPT teacher head0.205
Teacher spread0.165 · 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 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

Citations5
Published2018
Admission routes1
Has abstractyes

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