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Record W4416790073 · doi:10.1080/1081602x.2025.2593839

Finding families near and far in Canada and the United States

2025· article· en· W4416790073 on OpenAlexaboutno aff
Evan Roberts

Bibliographic record

VenueThe History of the Family · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicParental Involvement in Education
Canadian institutionsnot available
Fundersnot available
KeywordsPopulationInequalityGovernment (linguistics)

Abstract

fetched live from OpenAlex

This special issue highlights recent work in the history of families in Canada and the United States. With full-count census data series from the mid-nineteenth century newly available for both countries since the mid-2010s, this issue shows how scholars are taking advantage of new possibilities for research in North American family history. The articles in this issue return to several important questions in the history of families on the continent. How did families adapt to high rates of migration over long distances, with many people moving to destinations several weeks travel from their original homes? In early and late adulthood, what have been the changing patterns of living independently, or choosing to live with parents, adult children, or relatives outside the direct line of descent? The distinctive regional and cultural patterns of fertility change in North America are also discussed. Methodologically the issue demonstrates how historians of the family are using recently-released large census datasets in distinct ways. Some are taking advantage of the ability to create new variables or measures from microdata. Others focus on particular areas of the continent, and integrate large-scale data with other sources. Linkage to other record sources is also increasingly common.

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)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.400
Threshold uncertainty score0.407

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.034
GPT teacher head0.268
Teacher spread0.234 · 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 designQualitative
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
Published2025
Admission routes1
Has abstractyes

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