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Record W3122802892 · doi:10.2307/3270650

Evidence on Adverse Selection and Establishment Size in the Labor Market

2002· article· en· W3122802892 on OpenAlexaff
Harry Krashinsky

Bibliographic record

VenueIndustrial and Labor Relations Review · 2002
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicLabor market dynamics and wage inequality
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAdverse selectionSelection (genetic algorithm)Market sizeEconomicsActuarial scienceComputer science

Abstract

fetched live from OpenAlex

A commonly suggested explanation for the finding that laid-off workers have greater mean post-displacement earnings losses than workers who lose their jobs through plant closings is that the former are of lower quality than the latter. But there is also an alternative explanation for this result: laid-off workers suffer larger earnings losses because, as a group, they have more to lose in the first place, having been displaced from larger, higher-wage establishments. An analysis of data from the National Longitudinal Survey of Youth confirms this hypothesis. Accounting for establishment size removes virtually all of the difference in wage losses for the two groups of displaced workers.

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)0.002
metaresearch head score (Gemma)0.002
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.648
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.087
GPT teacher head0.259
Teacher spread0.172 · 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 designObservational
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

Citations13
Published2002
Admission routes1
Has abstractyes

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