Determinants of Childbearing Conceptions in Married Women: A Machine Learning Comparative Study
Abstract
In recent years, with the continuous progress of society and the continuous change of people's way of thinking, the inclusiveness of society towards women, especially married women, is increasing, and married women have gained more rights and choices, but the fertility rate in China is declining. As a result, the study of demographics and family structure has been gaining traction, especially on the decline in the natural growth rate of the population shown in the national census data, which is also related to the overall characteristics of women, such as whether they are employed or not. This paper uses multiple regression model, decision tree, random forest, gradient boosted regression tree model, support vector machine, XGboost and other machine learning models to train and compare the data, and draws the following conclusions: (1) The comprehensive characteristics of married women such as employment, age, and mother's education level are negatively correlated with their willingness to have children; (2) The influence of married women's husband's husbands and family characteristics on the intention to have children was positively significant. (3) Based on the results of multiple regression models, it warns us that we should consider multiple aspects when doing research or model selection, and that the selected model is good but not necessarily the most consistent with the characteristics of the data; (4) Based on the comparison of various models, it is found that the gradient boosted regression tree model, K-nearest neighbor model, XGBoost model and random forest model are better than the linear regression model.
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Introduction
In recent years, with the continuous progress of society and the profound transformation of people's thinking patterns, the tolerance and respect for women, especially married women, have been increasing. This change has given married women more choices and rights, however, China's fertility rate has shown a downward trend in this context, and changes in demographics and family structure have attracted more and more attention from all walks of life. In particular, the declining natural population growth rate revealed by the national census data is closely related to individual characteristics such as women's employment status, which is reflected in the fact that married women begin to consider whether to have children. Among them, the employment status, age, education level, and the relationship between various personal and family characteristics of married women are of great significance for understanding the dynamics of social fertility, promoting women's career development, and optimizing family policy formulation. In this context, it is crucial to use modern machine learning techniques to dig deeper into this topic. In addition, this study not only helps us to comprehensively examine and improve the social reproductive environment from the unique perspective of married women, but also has great significance for the exploration of women's career development, the change of family structure, the optimization of social labor structure, and the improvement of the overall level of China's economic and social development.
Conclusion
Based on the research on the comprehensive characteristics of married women and whether they have children aged 0-6 years old and other methods such as machine learning, this paper draws the following conclusions: (1) A series of comprehensive characteristics such as employment status, age level, and mother's education level of married women have a significant negative correlation with the decision of whether to have children aged 0-6. In other words, these characteristics will influence to some extent whether married women choose to have children. Specifically, as married women increase in employment, age, and mothers become more educated, their willingness to have children appears to be decreasing, leading to a corresponding decrease in the number of children aged 0-6 years. (2) The characteristics of married women's husbands and the characteristics of the family as a whole had a positive and significant impact on whether they had children aged 0-6 years. This means that when married women have good husbands and good family characteristics, they are more inclined to want married women to have children aged 0-6 years, and it is worth noting that the higher the education level of the father of a married woman, the positive impact on his or her childbearing. This finding seems to hint at a general psychological tendency that men, whether as husbands or fathers, expect married women to be able to have young children to some extent. (3) Based on the results of multiple regression model, it is found that when conducting research or selecting models, it is necessary to fully consider various possible influencing factors and conduct a comprehensive analysis. Avoid subjective selection of models, but there is a real possibility that they do not fully match the characteristics of the data. Therefore, before making a decision, it is necessary to carefully evaluate the pros and cons of various models to ensure that the research or prediction can achieve better results. (4) After comparing various models, it is found that the gradient boosted regression tree model, K-nearest neighbor model, XGBoost model and random forest model are significantly better than linear regression models. The results suggest that when dealing with complex data problems, more diverse models and algorithms should be tried to find the most suitable solution for the data characteristics, so as to better capture the nonlinear relationships and latent features in the data, so as to provide deeper and more comprehensive insights for research. The research in this paper has the following three policy implications:
First, policies tend to encourage childbearing. In order to effectively encourage childbearing, policymakers should focus on improving the family situation of married women, thereby motivating them to have children. Specifically, a series of measures such as information platform sharing and sharing sessions can be used to promote married women and their husbands to receive a higher level of university education, so as to improve the education level of the whole family. In order to better broaden their horizons and enhance the efficiency and competitiveness of families in production and life. At the same time, by improving family productivity, such as providing a family-friendly working environment and a flexible work system, the pressure on married women between home and the workplace can be further reduced, and a more relaxed and suitable environment for them to have children can be created.
Second, to promote women's employment, we should take practical and effective measures to protect women's equal rights and interests in the workplace based on the reality of their family situation. This includes, but is not limited to, promoting equity in employment in society and ensuring that women are not discriminated against or excluded on the basis of their gender. At the same time, the principle of fairness should be promoted within the family to avoid placing the responsibility of raising young children entirely on the shoulders of women, thereby limiting their career choices and career development. Men should be encouraged to participate more in family life, share childcare responsibilities and create a more equal and free employment environment for women.
Third, married women should fully consider their age when choosing to have children. Because as you get older, the risks and difficulties you face in having children also increase. Therefore, it is advisable for married women to plan their family plans as early as possible within the appropriate age range to ensure the health and safety of themselves and their children. At the same time, society should also provide more reproductive support and protection for married women, such as providing highquality medical resources and parenting guidance, so as to help them better cope with various challenges in the reproductive process.
Fourth, when analyzing the data used in this paper, we should take a comprehensive and detailed comparative analysis approach. By comparing the similarities and differences between different data, we can gain a deeper understanding of the nature and laws of the problem. At the same time, in order to find the most suitable analysis model, we also need to explore and try in many aspects based on the actual situation. The same principle applies to other research work. We should always maintain objectivity and rigor when analysing and processing data to ensure the accuracy and reliability of the research results.