Feminist political analysis: Exploring strengths, hegemonies and limitations
Bibliographic record
Abstract
Austerity politics, war in the Middle East and at other borders of the European Union, the rise of nationalisms, the emergence of populist parties and politicians, Islamophobia and the refugee crisis are amongst the recent developments suggesting the need for discussions about the theories and concepts that academic disciplines provide for making sense of societal, cultural and political transformations. In this article, we focus on the capacities of feminist political theories to undertake this task. By assessing different feminist approaches to political analysis that range from focusing on women and men, to analysing gender, to doing intersectionality and to adopting post-structural and new materialist approaches, we explore the contributions and the limitations of each framework. This allows us to consider where feminist theoretical debates on gender and politics currently are, to assess old and new developments and to address lacunae in the debate. Our argument is that dominant approaches in political science influence the emergence and marginalisation of particular feminist frameworks for political analysis, but also that feminist theorising of gender and politics, in striving for recognition within mainstream political science, reproduces its own hegemonies and marginalisations.
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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 | 0.064 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.010 | 0.048 |
| Scholarly communication | 0.016 | 0.017 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".