The effect of women in government on population health: An ecological analysis among Canadian provinces, 1976–2009
Bibliographic record
Abstract
Previous research finds connections between women in government, promotion of women's issues, and government spending. However, the connection between female politicians and population health warrants more significant attention. This study takes advantage of differences among Canadian provinces to evaluate the effect of women in government on age-standardized all-cause mortality rates, to assess the potential mediating role of government spending, and to determine the role played by political partisanship. Time-series cross-sectional data are retrieved from the Canadian Socio-Economic Information Management System II Tables for 1976-2009 (10 provinces and 34 years = 340 cases). Cumulative women in government is measured as the cumulative seats held by female politicians as a percentage of provincial seats since 1960. Political partisanship is measured as the cumulative seats held by female politicians in left-wing, centre, and right-wing parties as a percentage of provincial seats since 1960. Government spending is measured as the average of standard scores of four provincial expenditures: medical care, preventive care, other social services, and post-secondary education. Health is measured as total, male and female age-standardized mortality rates per 1000 population (all causes of death). Estimation techniques include the Prais-Winsten regressions with panel-corrected SEs, a first-order autocorrelation correction model, and fixed-unit effects, adjusted for alternative factors. We find that as the cumulative average percentage of women in government has historically risen, total, male, and female mortality rates tend to be lower, net of alternative explanations. Government spending partially mediates the effect of women in government on mortality rates. Moreover, increases in female politicians from left-wing, centre, and right-wing parties are all significantly associated with decreases in mortality rates. Women in government can bring about desirable changes in population health. Our work encourages more debate and research about quotas and other measures designed to level the political playing field for women.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".