The Spouse in the House: What Explains the Marriage Gap in Canada?
Bibliographic record
Abstract
Abstract. A literature has emerged in American voting studies noting a “marriage gap”—the propensity for married voters to support the Republican party. Using Canadian Election Study data, we establish the existence of a significant marriage gap in Canada. We also seek to determine if the marriage gap is driven by socio-demographic factors or attitudinal ones. We find that while socio-demographic factors contribute to the marriage gap, they explain relatively little variance. In probing the attitudinal basis of the marriage gap further, we find that married Canadians differ from the unwed very strongly on issues of moral traditionalism, but much less so on other issues that measure generalized conservatism. Résumé. Des travaux sont apparus dans les études américaines sur le vote remarquant l'existence d'un “écart mariage” (marriage gap) – la tendance des électeurs mariés à soutenir le parti républicain. Utilisant des données sur les élections nationales canadiennes, nous établissons l'existence d'un écart significatif au Canada. Nous cherchons aussi à déterminer si ce phénomène est poussé par les facteurs socio-démographiques ou les facteurs d'attitude. Nous constatons que bien que les facteurs socio-démographiques contribuent à cet écart, ils n'expliquent que relativement peu de variation. En recherchant davantage la base attitudinale, nous constatons que les canadiens mariés diffèrent très fortement de ceux qui ne sont pas mariés sur les questions de traditionalisme moral, mais cependant beaucoup moins sur les questions de conservatisme géneral.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".