Lobbying Beyond the Legislature: Challenges and Biases in Women's Organizations’ Participation in Rulemaking
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 study, which is based on a survey of women's organizations’ staff members, answers two previously unexamined questions about women's groups’ participation in the rulemaking process: (1) How do women's organizations participate? (2) What are the characteristics of the women's organizations that are the most likely to participate? About one-quarter (27%) of women's organizations reported that they lobby rulemakers, often using relatively low-cost methods, such as submitting comments or signing on to comments written by coalitions or like-minded groups. Women's organizations with large staffs that are structured the most like political insiders or influential economic interest groups were the most likely to participate in the process, potentially biasing participation in favor of relatively advantaged subgroups of women. Together, these results suggest that although rulemaking presents unique opportunities to represent women, the most marginalized women may be underrepresented during rulemaking debates.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 it