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Record W4254902863 · doi:10.1086/704046

Jacob Mincer Award

2019· article· en· W4254902863 on OpenAlex

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A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Labor Economics · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicLabor market dynamics and wage inequality
Canadian institutionsnot available
Fundersnot available
KeywordsMedalEconomic historySchools of economic thoughtThe artsEconomicsSociologyPolitical scienceHistoryArt historyNeoclassical economicsLaw

Abstract

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Previous articleNext article FreeJacob Mincer AwardPDFPDF PLUSFull Text Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinked InRedditEmailQR Code SectionsMoreDavid Card is the 2019 recipient of the Jacob Mincer Award for lifetime contributions to the field of labor economics. Card is the Class of 1950 Professor of Economics and the director of the Center for Labor Economics at the University of California, Berkeley. He is a fellow of the Society of Labor Economists, the Econometric Society, and the American Academy of Arts and Sciences. David has won numerous prizes and awards, including the Frisch Medal from the Econometric Society, the IZA Prize in Labor Economics, and the BBVA Foundation Frontiers of Knowledge Award. He has served as coeditor of the Journal of Labor Economics, the American Economic Review, and Econometrica. David has also served as president of the Society of Labor Economists and of the Western Economics Association.David grew up on a farm near Guelph, Ontario, and he attended a one-room school as a child. He was an undergraduate at Queens University and received his PhD in economics from Princeton. After spending one year on the faculty at the University of Chicago, David returned to Princeton in 1983, where he remained until 1997, when he moved to Berkeley. David’s time at Princeton was marked by, among other things, very fruitful collaborations with Orley Ashenfelter and Alan Krueger. It was at Princeton that David first exhibited his lifelong devotion to training graduate students. Many of David’s students, from both Princeton and Berkeley, are now leading economists in labor economics and related fields.David is an obvious choice for the Mincer Award. It is hard to think of a labor economist who entered the profession in the past 40 years with broader reach and influence than David Card. He has been a major force and leader in the field of labor economics for more than three decades with pioneering and influential contributions spanning all aspects of the field, and it is difficult for anyone to work in labor economics without citing his important work. David’s research stands as an exemplar of how empirical research in economics should be conducted.Any list of the substantive questions David has worked on will necessarily be incomplete due to the range of topics he has addressed, and we mention only some here. David’s research portfolio includes work on static and intertemporal labor supply, labor contracts and union wage and employment determination, the empirical methodology of estimating returns to schooling, the effects of school inputs (school quality) on earnings and racial wage gaps, long-run changes in racial wage gaps, the effects of immigration on the labor market, the effects of training and employment policies, the minimum wage, the empirical methodology of program evaluation and natural experiments, unemployment and unemployment insurance, and, most recently, the use of employer-employee matched data to examine the role of firms in wage setting and to test models of labor contracting.David’s earliest work was on indexation in labor contracts and on labor demand in a unionized environment. His interest in labor unions presaged his important later work on labor unions and inequality. David’s paper with Orley Ashenfelter on estimating the effect of training programs remains one of the important early contributions to the literature on program evaluation. David’s work with John Abowd on employment contracts and models of earnings and labor supply stands as seminal work on these problems. David’s work on immigration began with his well-known study of the effects of the Mariel boatlift on the Miami labor market and stands as a prime example of the use of a natural experiment to understand an important policy problem. This work was followed by his later central contributions to the literature on the effects of immigration. David’s seminal work with Alan Krueger on the employment effects of the minimum wage challenged conventional orthodoxy, changed the way economists thought about the minimum wage, and was an important driver in subsequent work on employer market power and monopsony. David’s work on education, focusing both on the role of educational resources and on understanding the causal effect of education on earnings, consists of central contributions to the human capital literature. More recently, David’s work on heterogeneity across firms in wage setting has played an important role in understanding wage inequality.In conclusion, the depth and breadth of David Card’s contributions to labor economics, his mentoring of generations of students who have gone on to be the leaders of succeeding generations of labor economists, and his generous provision of professional public goods to the field and to the Society of Labor Economists make him an ideal recipient of the Jacob Mincer Award.2019 Jacob Mincer Award Nominating Committee:Joseph Altonji (ex officio)Henry Farber (chair)John HaltiwangerHilary HoynesLawrence KatzAlan ManningPetra Todd Previous articleNext article DetailsFiguresReferencesCited by Journal of Labor Economics Volume 37, Number 3July 2019 Published for the Society of Labor Economists, Economics Research Center/ NORC Article DOIhttps://doi.org/10.1086/704046 © 2019 by The University of Chicago. All rights reserved.PDF download Crossref reports no articles citing this article.

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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 categoriesInsufficient payload (model declined to judge)
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 score0.516
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.015
GPT teacher head0.215
Teacher spread0.200 · 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