MétaCan
Menu
Back to cohort
Record W2162672782

What Has Happened to Middle-Class Earnings? Distributional Shifts in Earnings in Canada, 1970-2005*

2014· preprint· en· W2162672782 on OpenAlexaboutno aff
Charles M. Beach

Bibliographic record

VenueRePEc: Research Papers in Economics · 2014
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicLabor market dynamics and wage inequality
Canadian institutionsnot available
Fundersnot available
KeywordsEarningsMicrodata (statistics)Middle classDemographic economicsPercentileEarnings per shareLabour economicsCensusEconomicsDemographyPopulationAccountingSociologyStatisticsMathematics
DOInot available

Abstract

fetched live from OpenAlex

This paper examines how middle-class earnings in Canada have changed between 1970 and 2005 using Census microdata. Middle-class earnings are defined as workers’ earnings between 50 and 150 percent of the median or as earnings between the 20th and 80th percentile earnings. The analysis looks at the proportion of workers (“workers’ share†) with middle-class earnings and the proportion of earnings (“earnings share†) received by middle-class workers. The study finds: (i) there has been a marked decline of full-time full-year middle-class workers and corresponding marked increases of higher- and lower-earning workers in the Canadian workplace; (ii) there has been an even larger shift in earnings with middle-class workers losing out to strong earnings gains of higher-earning workers; and (iii) the majority of the decline of the middle-class earnings share was due to the fall in their workers’ share for male and for full-time full-year female 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 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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.436

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.010
Science and technology studies0.0030.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.045
GPT teacher head0.266
Teacher spread0.221 · 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 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

Citations1
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueRePEc: Research Papers in EconomicsSame topicLabor market dynamics and wage inequalityFrench-language works237,207