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Record W4254151510 · doi:10.4095/301519

Sex Composition (female) by Marital Status, 2006 - Widowed (by census division)

2010· report· en· W4254151510 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typereport
Languageen
FieldSocial Sciences
TopicDemographic Trends and Gender Preferences
Canadian institutionsnot available
Fundersnot available
KeywordsCensusMarital statusDemographyDivision (mathematics)Composition (language)GerontologyGeographyPsychologySociologyMedicineMathematicsPopulationArt

Abstract

fetched live from OpenAlex

In 2006, 49.4% of males and 46.5% of females aged 15 years and over were legally married (and not separated), while 2.7% of the males and 3.2% of the females were separated, but still legally married. The male and female proportions for divorced people were 7.2% and 8.8% respectively. The gender gaps in the widowed and never married categories were larger: 2.5% of males and 9.7% of females were widowed while 38.2% of males, but only 31.8% of females were never legally married. In the case of the never married population 15 years of age and over, the highest proportions occurred in Quebec (46.8% of men and 40.0% of women), and the three territories (Yukon: 46.6% of men and 40.7% of women; Northwest Territories: 54.4% of men and 49.4% of women; and Nunavut: 63.4% of men and 59.2% of women). On the other hand, the sexual divergence of rates between males and females never legally married was highest in Alberta (37.7% of males versus 30.4% for females or a 7.3% difference) and Saskatchewan (36.6% of males versus 29.3% for females or a 7.3% spread). For the widowed population, this disparity was most pronounced for Saskatchewan (2.7% widowers versus 11.6% widows or an almost 9% difference). The map shows by census division the marital status of the population 15 years of age and over by gender.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.753
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.036
GPT teacher head0.332
Teacher spread0.296 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2010
Admission routes1
Has abstractyes

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