The Impact of Gender Factors on Economic Development: A Global Comparative Analysis
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Bibliographic record
Abstract
The purpose of this study is to determine trends and the current state of the gender issue, as well as the impact of different gender factors, taking into account the period of COVID-19, on the level of Ukrainian GDP compared with the countries of the world in modern conditions and to propose appropriate recommendations for the activation and stimulation of women’s participation in business. The authors emphasize that women are disproportionately affected by various social crises: climate change, wars, conflicts and human rights violations etc. The authors analyze the Ukrainian Gender Inequality Index in and make a conclusion that it more than halved during the last decades. The reason for this, especially in recent years, was the COVID-19 pandemic and the subsequent full-scale Russian invasion of Ukraine that had a very negative impact on business. The authors note that Ukraine is situated in 35th place in the European ranking of countries concerning the value of the Gender Inequality Index. A large number of women are generally not involved in the labor market or other economic activities. At the same time, a continuing consequence of the Russian full-scale invasion of Ukraine was a noticeable lack of qualified personnel on the labor market. This is due to the involvement of exclusively men in certain sectors of the economy and their mobilization. The results of the regression analysis indicate that economic participation has the greatest impact on GDP among all the components of the Global Gender Gap Index in the USA, Canada and Poland. Educational attainment is situated on the second place. As for Ukraine, the authors show that as the level of participation of women in the labor force increases, Ukrainian GDP also increases. Taking into account the results of the calculations, the authors conclude that gender factors have a direct impact on the country's economy Keywords: gender factors, sustainable development, gender equality, Gender Inequality Index, Global Gender Gap Index, GDP, Ukraine, Poland, The USA, Canada.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it