The attitude of Ukrainian society toward equal rights and opportunities in the military sphere
Bibliographic record
Abstract
Ensuring gender equality in general and in the military sphere during wartime is an important component of democratic development, particularly in Ukrainian society. At the beginning of the article, the international and Ukrainian experience of ensuring equal rights and opportunities in the military sphere was studied; the experience of integrating women into the armed forces of such countries as Norway, Israel, the United States of America, and Canada is systematized. The peculiarities of the involvement of women in the military sphere of Ukrainian society from a historical perspective are clarified.What do Ukrainians think about the involvement of women in the military, especially during the Russian-Ukrainian war and after the full-scale invasion? The empirical part of the work is based on the analysis of quantitative data obtained as a result of three representative surveys from the Kyiv International Institute of Sociology (KIIS) in 2018 and the research agency “Info Sapiens” in 2023 and 2024. Accordingly, the dynamics of Ukrainian society’s attitude to gender equality in the military sphere in 2018, 2023, and 2024, including, depending on socio-demographic indicators, were revealed. Finally, the public opinion of the Ukrainian society about the option of the army, which should be introduced in Ukraine, was studied.The results of a survey of Ukrainian society over the last six years of the Russo-Ukrainian war demonstrate wave-like support for egalitarian ideas regarding the policy of equal rights and opportunities in the military sphere. One year after the full-scale invasion (in 2023), support increased, and two years later (in 2024), it was back to 2018 levels.In general, more than half of surveyed Ukrainians, both men and women, support the statement that women should be given equal opportunities with men to work in the Armed Forces of Ukraine (AFU) and other military formations. The level of support is higher among those with higher education as well as among people in the older age group.It is important to add that, among other things, this is influenced by the historical persistence of the tradition of women’s participation in combat operations, which has been traced since the First World War.Ukrainian society supports the idea of a rather American model of the army – the conscription of both men and women only voluntarily (under contract). On the other hand, support for the Israeli model – the conscription of all men and all women – is very low. The current version of the army – the conscription of all men and only some women – is also not very popular in Ukrainian society.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".