NATO's About-Face: Adaptation to Gender Mainstreaming in an Alliance Setting
Bibliographic record
Abstract
Abstract Scholars in global security studies have only recently focused attention on how and why international security organizations (ISOs) adapt. Since the United Nations Security Council's issuance of Resolution 1325, some ISOs have enacted changes to implement gender mainstreaming. The concept involves incorporating gender-based analyses in policy and planning and increasing women's representation. Drawing on interviews with seventy-one elites and a dataset of ninety-seven NATO gender guidelines, this article introduces an original argument for why NATO adapted to gender mainstreaming. Such adaptation is surprising given the military's historical resistance to gender considerations and that civilian bodies typically enact reforms. Findings indicate that other ISOs were substantially influential in the process and that institutional incentives built into NATO's military bodies drove military officials to implement mainstreaming in practice. Additionally, military elites perceived a link between gender mainstreaming and operational effectiveness, which further consolidated organization-wide adaptation. This study challenges long-held assumptions about militaries’ resistance to gender-related changes. It also offers one of the first empirical assessments of gender mainstreaming in an ISO.
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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 | 0.017 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| 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".