Federalism, Feminism and Multilevel Governance: Gender in a Global/Local World
Bibliographic record
Abstract
Until recently, few gender scholars took notice of the impact of state architecture on women's representation, political opportunities, and policy achievements. Likewise scholars of federalism, devolution and multilevel governance have largely ignored their gender impact. For the first time, this book explores how women's politics is affected by and affects federalism, whether in Australia, Canada, India, Mexico, Nigeria, Russia or the US. Equally, it assesses the gender implications of devolution and multilevel governance in the European Union, including case studies of the UK and Germany. Globally, multilevel governance is providing new arenas for women's politics. For example, CEDAW (the UN Convention for the Elimination of All Forms of Discrimination against Women) has led most governments to adopt gender-equality norms while other UN instruments have supported Aboriginal self-government. Gender scholars will find especially valuable what is revealed about the impact of political architecture on a broad range of policy issues, including gay marriage, reproductive rights and childcare. Federalism scholars will benefit from the book's wide range of cases, comparative themes and combination of gender and federalism perspectives. Written by leading experts, this book fills an important gap in both literatures.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".