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Record W4414892826 · doi:10.1080/01615440.2025.2556100

Measuring socioeconomic status in historical censuses of Canada

2025· article· en· W4414892826 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueHistorical Methods A Journal of Quantitative and Interdisciplinary History · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicUrban, Neighborhood, and Segregation Studies
Canadian institutionsBank of CanadaToronto Metropolitan UniversityUniversity of Toronto
FundersUniversité de MontréalUniversity of SaskatchewanUniversity of AlbertaUniversity of TorontoUniversity of New BrunswickUniversity of GuelphUniversity of Ottawa
KeywordsSocioeconomic statusCensusHistorical demographyDemographic analysisResearch methodologyPopulation

Abstract

fetched live from OpenAlex

We use the new complete count Canadian Census records spanning from 1871 to 1901 to explore measures of socioeconomic status including income, occupation, and literacy, which scholars commonly use to investigate economic mobility and inequality. We first explore the availability and comparability of measures across census years. Then, using individuals in the 1901 Census which contains wages, we document selection into the wage sample as well as the characteristics of individuals found in different segments of the wage distribution. Lastly, auxiliary status measures from social registers and probate records are explored for those in occupations where income is under-enumerated.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.685
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.119
GPT teacher head0.398
Teacher spread0.279 · 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