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Record W3123764729 · doi:10.1086/430288

Changes in U.S. Wages, 1976–2000: Ongoing Skill Bias or Major Technological Change?

2005· preprint· en· W3123764729 on OpenAlex

Why this work is in the frame

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

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Labor Economics · 2005
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Productivity
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTechnological changeHuman capitalWageEconomicsDifferential (mechanical device)Technical changeLabour economicsPhysical capitalDemographic economicsCapital (architecture)MacroeconomicsProductivityEconomic growthEngineering

Abstract

fetched live from OpenAlex

This article examines the determinants of changes in the U.S. wage structure from 1976 to 2000. Our main empirical observation is that changes in both the level of wages and the returns to skill over this period were primarily driven by changes in the ratio of human capital to physical capital. We show that this pattern conforms extremely well to a simple model of technological adoption following a major change in technological opportunities. In contrast, we do not find much empirical support for the view that ongoing (factor‐augmenting) skill‐biased technological progress has been an important driving force over this period.

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.

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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.624
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.092
GPT teacher head0.253
Teacher spread0.161 · 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