Good Girls Go to the Polling Booth, Bad Boys Go Everywhere
Bibliographic record
Abstract
Participation research routinely reveals a gender gap with regard to most forms of political engagement. In the recent literature, differences in the availability of resources and civic skills are usually invoked as an explanation for this pattern. This theory focuses primarily on adult behavior and has not as yet been investigated among young people, for whom we can assume that resources are distributed more equally. In this article, we examine gender differences in the anticipation of political participation among American fourteen-year-olds, building on the 1999 International Association for the Evaluation of Educational Achievement study (n = 2,811). First, the results show that girls at this age mention even more actions they intend to engage in than do boys, so clearly the gender gap with regard to the level of participation has not yet emerged at that age. Second, we observe distinct patterns with regard to the kinds of actions favored, with girls being drawn more towards social movement-related forms of participation than boys, and with boys favoring radical and confrontational action repertoires as compared to girls. The results are important for the reconceptualization of the concept of political participation as well as for theories that explain the gender gap.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.036 | 0.003 |
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".