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Galbraith, John Kenneth (1908–2006)

2014· other· en· W1502356317 on OpenAlexaboutno aff
Conrad P. Waligorski

Bibliographic record

VenueThe Encyclopedia of Political Thought · 2014
Typeother
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Theory and Institutions
Canadian institutionsnot available
Fundersnot available
KeywordsSchools of economic thoughtPovertyGovernment (linguistics)Power (physics)EconomicsPoliticsPublic policyEconomic historyPublic administrationPolitical scienceNeoclassical economicsLawEconomic growth

Abstract

fetched live from OpenAlex

Abstract John Kenneth Galbraith (1908–2006) was a reform liberal activist, economist, and public intellectual who identified with John Maynard Keynes's economics and public policy goals, but criticized neoclassical economics and Keynesian accommodation with neoclassical economics. He claimed conventional economics ignores interconnections between politics and economics, affluence, large corporations, power, poverty, inequality, and government's necessary role in a modern economy. In more than 30 books, scores of articles, and decades of congressional testimony, Galbraith expressed general propositions and principles while trying to influence public opinion and policy. Born in Canada, in 1931 he received a PhD from the University of California, Berkeley, and spent most of his academic career at Harvard University. Public positions included ambassador to India, 1961–63, advising presidents Kennedy and Johnson, and influencing Johnson's “war on poverty.”

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)0.002
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.034
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0020.002
Scholarly communication0.0040.004
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0340.019

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 head0.017
GPT teacher head0.230
Teacher spread0.213 · 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
GenreOther

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
Published2014
Admission routes1
Has abstractyes

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