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Record W7098887185

1Immigration and Canada’s Wage Structure in the First Half of the Twentieth Century

2008· article· en· W7098887185 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicEducation, Innovation and Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsWageDistribution (mathematics)Wage dispersionImmigrationReal wagesEfficiency wageCensus
DOInot available

Abstract

fetched live from OpenAlex

In an earlier paper, (Green and Green (2007)), we presented evidence using Census data on movements in the Canadian wage structure between 1911 and 1941. That evidence pointed to a substantial widening in the Canadian wage structure in the early twentieth century. More specifically, between 1911 and 1921 real wages fell at both the top and bottom ends of the wage distribution while in the following decade the wages at the bottom stayed relatively constant while the wages at the top end increased dramatically. Finally, during the 1930s, the spread of the wage distribution remained relatively constant. This broadening of the distribution is in striking contrast to the description of substantial compression in the US wage distribution over this same period presented in Goldin and Katz(2001). In particular, the two countries had substantially different experiences in terms of movements in their wage structure in the 1920s, with dispersion expanding substantially for Canada but not for the US. Understanding what forces drove these very different wage trends is potentially useful as an input into a better understanding of differences in technological choices in the two countries and, thus, of the different paths of economic growth in each. We argue in our earlier paper that the difference in immigration experiences between

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.258
Threshold uncertainty score0.343

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.013
GPT teacher head0.261
Teacher spread0.249 · 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.

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

Citations0
Published2008
Admission routes1
Has abstractyes

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