Attitudes towards women in the military and their relation to both quantity and quality contact with female leaders
Bibliographic record
Abstract
Contact experiences with women in senior leadership roles are important for creating acceptance of women in organizations dominated by men, such as the military, as leadership roles are considered demanding, requiring numerous agentic qualities that are often ascribed to men. The military lacks women in leadership levels within its organization. We wished to determine whether quality and quantity contact with women in leadership positions reduces intergroup anxiety, increases empathy and perspective-taking, and subsequently creates more favorable attitudes toward women in the military. This was examined in three studies, one with a military sample consisting of men (n = 95), another with a civilian sample of men (n = 367), and a third study with a civilian sample of women (n = 374). Our findings revealed that quality contact was related to attitudes toward women in the military for all three samples. Results from the indirect effects tests conducted for the civilian male and female samples revealed that for civilian men, intergroup anxiety demonstrated a significant indirect effect between quantity contact and attitudes toward women in the military, while both intergroup anxiety and perspective-taking demonstrated significant indirect effects between quality contact and attitudes toward women in the military. Furthermore, both quantity and quality contact demonstrated significant direct effects. On the other hand, results revealed that for civilian women the only significant relation was the direct effect between quality contact and attitudes toward women in the military. Intergroup anxiety, perspective-taking, and empathy did not demonstrate any indirect effects for the civilian women sample. Thus, given that interactions with women in leadership positions are related to views of women in the military, research should further explore the role of contact for women in non-traditional work roles.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".