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Record W4407260429 · doi:10.1017/s1053837224000488

POST-KEYNESIAN ECONOMICS AS DEFENSE MECHANISM: SIDNEY WEINTRAUB AS KNOWN BY E. ROY WEINTRAUB

2025· article· en· W4407260429 on OpenAlexaff
Till Düppe

Bibliographic record

VenueJournal of the History of Economic Thought · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Theory and Policy
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsDistancingMainstreamPost-Keynesian economicsPsychoanalysisIdentity (music)EconomicsSociologyPositive economicsNeoclassical economicsPhilosophyKeynesian economicsPsychologyCoronavirus disease 2019 (COVID-19)TheologyMedicine

Abstract

fetched live from OpenAlex

This article traces the evolution of Sidney Weintraub’s Post-Keynesian identity during the four decades following WW II, as seen through the eyes of his son E. Roy Weintraub. I explore Roy’s notion that Sidney’s career can be seen as the result of defense mechanisms associated with those of a borderline personality, such as splitting and projection. As Sidney transformed from an aspiring mainstream macroeconomist into a reclusive warrior for ideas, developing a polarized view of the economics profession, his work eventually became subsumed as a branch of Post-Keynesian economics. At the same time, he nudged his son into a symbiotic dependency, standing in for his career as a mathematical economist and coauthor, while also being made complicit in his adultery. Roy’s eventual distancing from this role ultimately led to a rupture prior to Sidney’s death in 1983. It was only then that Roy was able to establish a scholarly profile as a historian of economics and gain the understanding of his father that informs this text.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.010
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.011
GPT teacher head0.208
Teacher spread0.197 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2025
Admission routes1
Has abstractyes

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