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Record W1964288435 · doi:10.1353/cjs.2006.0015

Twentieth-Century Trends in Occupational Attainment in Canada

2005· article· en· W1964288435 on OpenAlexaffvenueabout
Richard A. Wanner

Bibliographic record

VenueThe Canadian Journal of Sociology · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicIntergenerational and Educational Inequality Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMultinomial logistic regressionSocioeconomic statusOccupational prestigeEducational attainmentOrdinary least squaresLogistic regressionDemographyRegression analysisOccupational mobilityDemographic economicsSociologyGeographyEconomicsEconometricsStatisticsEconomic growthPopulationMathematics

Abstract

fetched live from OpenAlex

Has the increase in educational attainment in Canada over the course of the twentieth century served to loosen the ascriptive links between status of family of origin and their own occupational status among Canadian men and women? Using data from the 1973 Canadian Mobility Study and the 1986 and 1994 Statistics Canada General Social Surveys, I address this question by applying two complementary methods, one applying OLS regression and the other a multinomial conditional logit (MCL) model. The regression results indicate that for men the effect of socioeconomic origins declined considerably in Canada during the twentieth century, as did the effect of language for both men and women. However, the effect of education on occupational status was unchanged for both men and women. Findings from the MCL models are generally consistent with the regression results, but show that the decline in the effect of father's occupation among men is largely the result of an increased flow between occupational categories rather than a decline in immobility.

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)0.002
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 score0.035
Threshold uncertainty score0.253

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.008
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.061
GPT teacher head0.344
Teacher spread0.283 · 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

Citations11
Published2005
Admission routes3
Has abstractyes

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Same venueThe Canadian Journal of SociologySame topicIntergenerational and Educational Inequality StudiesFrench-language works237,207