Gender analysis of the Spanish Fertility Survey 2018

• Published in: Gaceta sanitaria Vol. 36; no. 3; p. 221
• Main Authors: Pérez Corral, Olivia, Danet Danet, Alina
• Format: Journal Article
• Language: Spanish
• Published: Spain 01.05.2022
• Subjects: Child; Female; Fertility; Humans; Language; Male; Pregnancy; Sex Factors; Sexual Behavior; Socioeconomic Factors; Surveys and Questionnaires; Gender analysis; Survey; Encuestas; Fertility; Sesgos de género; España; Análisis de género; Gender bias; Fecundidad; Spain
• ISSN: 1578-1283
• DOI: 10.1016/j.gaceta.2021.03.005

To analyze the language and content of the questionnaire used in the Fertility Survey 2018, from a gender perspective. Qualitative design based on a content analysis of the questionnaire used in the Fertility Survey 2018. Methodological recommendations and guides for gender-sensitive statistics were used, together with the comparison established with the Generations and Gender Survey. The categories of analysis were: language, sexual division of labor and fertility. The analysis procedure included the checklist and the incorporation of emerging variables specifically related to gender inequalities and biases. The questionnaire uses with some inclusive language, but maintains the generic use of masculine gender, reproduces gender stereotypes and uses male-female binomials as a single concept. It offers a limited perspective on sexual division of domestic and care labor, horizontal and vertical segregation in the workplace, gender differences between the access and control of resources. In relation to fertility, it reproduces gender inequalities and biases that build a normalized and idealized vision on having children, do not reflect the differential impact of pregnancy and parenting on women's health and prioritize the biological dimension of motherhood and fatherhood. The Spanish Fertility Survey needs to improve its gender sensitivity, reflect the heterogeneous biological, socio-economic and structural dimensions of fertility and explore deeper into the differential elements that generate inequalities and gender biases.