The Effects of Political Parties on Federal Level Appointment of Women: A Comparative Analysis of the United States and Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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 | 0.000 | 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 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it