What do Women Really Know? A Gendered Analysis of Varieties of Political Knowledge
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
While studies typically find that women know less about politics than do men, feminist scholars have argued that these findings reflect gender-biased measures that underestimate women's political knowledge. This article evaluates the feminist critique by taking a more expansive view of what constitutes political knowledge. Using data from a large Canadian urban sample, we show that gender gaps close or even reverse when people are queried about more practical aspects of political knowledge, such as government benefits and services. Our results also demonstrate that this type of knowledge is more equally distributed than its conventional counterpart, though the women who are the most likely to need government services and benefits are often the least likely to know about them. Finally, we show that knowledge of government services and benefits has a significant effect on women's intended vote choice. This article thus shows that more practical types of political knowledge might serve as meaningful additions to existing definitions and measures of political knowledge.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it