Bringing nations in: Some methodological and conceptual issues in connecting feminisms with nationhood and nationalisms
Bibliographic record
Abstract
The recent explosion of case studies about women's involvements in national projects reveals considerable diversity ranging from hostility and alienation, to affiliation or participation. Feminist analysis is just starting to explore the causes and effects of such diversity, however, since a single, common relationship usually was theorized between ‘gender’ and ‘nation’. This article addresses some methodological and conceptual issues concerning the systematic comparison of these diverse relationships. It is argued that comparison is required to explain ‘linkages between ideologies, religions and conflicts’ from a gendered perspective and to incorporate the wide variety of women's experiences regarding national projects. Especially significant in this diversity is that, while national projects in ‘the West’ are rarely a site for women's liberation and most ‘western’ feminists are alienated from nationalism, globally women are more often mobilized by national projects than any other form of politics (Bystydzienski 1992). Moreover, some women's movements affiliate with national projects with positive outcomes. To understand how women's diverse involvements in national projects affect domestic and international conflicts, we need to identify factors producing this diversity in gender/nation relationships. The article reports on a ‘test’ of six hypotheses concerning three modal cases drawn from a larger project eventually concerning thirty countries.
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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 | 0.068 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.015 | 0.094 |
| Scholarly communication | 0.016 | 0.021 |
| Open science | 0.006 | 0.012 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 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".