The Effects of Political Parties on Federal Level Appointment of Women: A Comparative Analysis of the United States and Canada
Bibliographic record
Abstract
abstract: This thesis comparatively examines the percentage of women who have been appointed to federal level Cabinet positions in the United States and Canada between 1980 and 2010. The thesis will first explain the differences in the nation's democratic systems -- presidential and parliamentarian -- to contextualize how each nation elects federal representatives coupled with their process of appointing individuals to Cabinet positions per administration. Then the thesis will briefly explain the basis of the political parties that have been active in each country alongside their prominent ideals, in an effort to understand the impact it has had on the number of women elected to federal positions. Finally, the research will focus on the number of women appointed to Cabinet to demonstrate how an increase in the amount of political parties, creates more competition between political parties, in turn allowing for a higher number of women to be elected as well as appointed to federal positions. In conclusion, the research suggests that liberal party's push forth more women to federal level positions in both countries. Coupled with the fact that the increase in the amount of office holding parties increases competition between parties and increases the number of women appointed to Cabinet.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".