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Record W1972281289 · doi:10.1080/10427710120049264

Where Else Would you Look? Constructivism and the Historiography of Economics

2001· article· en· W1972281289 on OpenAlexaff
Ross B. Emmett

Bibliographic record

VenueJournal of the History of Economic Thought · 2001
Typearticle
Languageen
FieldArts and Humanities
TopicPhilosophy and History of Science
Canadian institutionsGlenrose Rehabilitation Hospital
Fundersnot available
KeywordsHistoriographyEpistemologyConversationNaturalismPhilosophy of scienceKnightConstructivism (international relations)Relevance (law)Social scienceSociologyPositive economicsPhilosophyPolitical scienceLawPoliticsEconomicsInternational relations

Abstract

fetched live from OpenAlex

Eleven years ago, at my first HES conference, I attended a session on the historiography of economics. In my naiveté and brashness (not a good combination!) as a grad student, I asked why so much of the conversation about how to do historical work in economics was dominated by reference to methodological categories provided by philosophers of science like Lakatos, Popper, and Kuhn. I enjoyed my own investigations in the philosophy of economics, and was starting to write about Frank Knight, who was certainly not naive philosophically, but I wanted a different reference point as a historian of economics. I remember one member of the panel looking at me somewhat puzzled and asking, “Where else would you look?” Today, we gather to reflect, once again, on the historiography of economics. This time, we are asked to reflect on a new reference point for our work: the sociology of scientific knowledge or science studies. Jan Golinski has provided us with an excellent survey of work in this field, and a synopsis of its relevance over the past fifteen years or so to the history of the natural sciences. His book is not a rallying cry for constructivism, but rather a careful analysis of the benefits and costs to historians of science if they choose to adopt constructivist techniques.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.938
Threshold uncertainty score0.998

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 studies0.0000.004
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 head0.027
GPT teacher head0.187
Teacher spread0.160 · 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 designNot applicable
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

Citations1
Published2001
Admission routes1
Has abstractyes

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