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Record W3125650317

The Oxford Handbook of Economic Inequality

2011· preprint· en· W3125650317 on OpenAlexaboutno aff
Wiemer Salverda, Brian Nolan, Timothy M. Smeeding

Bibliographic record

VenueRePEc: Research Papers in Economics · 2011
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policy and Economic Growth
Canadian institutionsnot available
Fundersnot available
KeywordsWelfare stateInequalityState (computer science)SociologyVisionHumanitiesPolitical scienceEconomic historyArt historyLibrary scienceArtHistoryLawPoliticsAnthropology
DOInot available

Abstract

fetched live from OpenAlex

The Oxford Handbook of Economic Inequality presents a new and challenging analysis of economic inequality, focusing primarily on economic inequality in highly developed countries. Bringing together the world's top scholars this comprehensive and authoritative volume contains an impressive array of original research on topics ranging from gender to happiness, from poverty to top incomes, and from employers to the welfare state. The authors give their view on the state-of-the-art of scientific research in their fields of expertise and add their own stimulating visions on future research. Ideal as an overview of the latest, cutting-edge research on economic inequality, this is a must have reference for students and researchers alike. Contributors to this volume - Anders Bjorklund, Stockholm University Francine D. Blau, Cornell University Andrea Brandolini, Banca d'Italia Richard V. Burkhauser, Cornell University Gary Burtless, The Brookings Institution Daniele Checchi, L'Universita degli Studi di Milano Kenneth A. Couch, University of Connecticut James B. Davies, University of Western Ontario Gosta Esping-Andersen, Universitat Pompeu Fabra Francisco H.G. Ferreira, The World Bank Ada Ferrer-i-Carbonell, Institut d'Analisi Economica-C.S.I.C. Barcelona Nancy Folbre, University of Massachusetts Amherst Richard B. Freeman, Harvard University The Late Andrew Glyn, University of Oxford Mary B. Gregory, University of Oxford Markus Jantti, Abo Akademi University Christopher Jencks, Harvard University Stephen Jenkins, ISER, University of Essex Martin Kahanec, IZA, Bonn Lawrence M. Kahn, Cornell University Julia Lane, University of Chicago Andrew Leigh, Australian National University Claudio Lucifora, Universita Cattolica del Sacro Cuore Stephen Machin, University College London Ive Marx, University of Antwerp Nolan McCarty, Princeton University John Myles, University of Toronto Brian Nolan, University College Dublin Jonas Pontusson, Princeton University Martin Ravallion, The World Bank John E. Roemer, Yale University Wiemer Salverda, University of Amsterdam Timothy M. Smeeding, Syracuse University Philippe van Kerm, CEPS/INSTEAD Bernard van Praag, University of Amsterdam Jelle Visser, University of Amsterdam Sarah Voitchovsky, University of Oxford Klaus Zimmermann, IZA, Bonn

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.740
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.002
Research integrity0.0010.002
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 head0.094
GPT teacher head0.311
Teacher spread0.217 · 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

Citations19
Published2011
Admission routes1
Has abstractyes

Explore more

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