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Record W3170989152 · doi:10.1017/s1053837220000334

THE EMERGENCE OF GEOGRAPHICAL ECONOMICS: AT THE CONTESTED BOUNDARIES OF ECONOMICS, GEOGRAPHY, AND REGIONAL SCIENCE

2021· article· en· W3170989152 on OpenAlexaff
Jasmeen Rahman, Robert W. Dimand

Bibliographic record

VenueJournal of the History of Economic Thought · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicRegional Economics and Spatial Analysis
Canadian institutionsBrock University
Fundersnot available
KeywordsDisciplineLocation theoryMonopolistic competitionEconomic geographyStrategic geographyCritical geographyHistorical geographyFujita scaleAgricultural geographyUrban economicsHuman geographyTime geographySociologySocial scienceEconomicsNeoclassical economicsGeographyDevelopment geographyMonopoly

Abstract

fetched live from OpenAlex

We explore disciplinary boundary-making in geographical economics or “the new economic geography” with attention to the approaches taken by, and attempts at communication among, scholars with primary affiliations in economics, geography, and regional science. The Dixit-Stiglitz general equilibrium approach to monopolistic competition and increasing returns was applied to agglomeration and location by Paul Krugman, who had previously pioneered the “new trade theory” building on the Dixit-Stiglitz model, and, independently and slightly earlier, by Masahisa Fujita and his student Heshem Abdel-Rahman, starting from regional science, a tradition with its own departments, doctorates, conferences, and journals distinct from economics and geography. Economic geography, as studied by geographers, had already taken a quantitative and theoretical turn in the 1960s, reviving an earlier tradition of German location theory overshadowed within geography after World War II by areal differentiation. Another strand of economic geography pursued by geographers was influenced by economic theory but by non-neoclassical Marxian and Sraffian economics. Debates between these scholars raised questions whether these analyses were multidisciplinary, drawing on distinct disciplines, or crossed disciplinary boundaries (as when geographical economics in the style of economists is undertaken in geography departments) or transcends disciplinary boundaries, or involved the emergence of a new discipline.

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 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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.778
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.006
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.026
GPT teacher head0.205
Teacher spread0.179 · 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 teacher head, 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

Citations8
Published2021
Admission routes1
Has abstractyes

Explore more

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