The (M)otherhood trap: reconsidering sex, gender, and legislative recruitment
Bibliographic record
Abstract
Book snopsis: When women in politics interact with reporters, opponents, and constituents, they are forced to confront their parental status. If they have children, they are questioned about their competence in both their public and private lives. If they don’t, they face criticism for not understanding or relating to key policy domains. This “damned if you do, damned if you don’t” conundrum raises difficult questions about how politicians, voters, and the media navigate the intersection of gender, parental status, and politics. \n \nMothers and Others brings together scholars researching political careers, party organization, political behaviour and representation, and public policy to discuss the role of parental status in political life. They look at three main areas of citizen engagement with the political system – parenthood and political careers, parenthood in the media, and parenthood and political behaviour – to argue that being a parent is a gendered political identity that influences how, why, and to what extent women (and men) engage with politics. \n \nThe first major comparative analysis of the role of parenthood in politics, Mothers and Others makes important observations about what we know and what we still need to find out. \n \nMothers and Others is for scholars and students of political science, gender and women’s studies, and sociology both in Canada and abroad.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.017 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".