Gender Quotas and the Crisis of the Mediocre Man: Theory and Evidence from Sweden
Bibliographic record
Abstract
Efforts to increase female political representation are often thought to be at odds with meritocracy. This paper develops a theoretical framework and an empirical analysis to examine this idea. We show how the survival concerns of a mediocre male party leadership can create incentives for gender imbalance and more incompetent men in office. The predictions are tested with data on candidates in Swedish municipalities over seven elections (1988-2010), where we use admin-istrative data on labor-market performance to craete a measure of the competence of politicians. We investigate the effects of the "zipper" quota, requiring party groups to alternate male and female names on the ballot, unilaterally implemented by the Social Democratic party in 1993. Far from being at odds with meritocracy, this quota increased the competence of male politicians where it raised the share of female representation the most. ∗The authors thank seminar participants at Science-Po, Harvard, Stockholm University,
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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 | 0.023 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.034 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".