Back to Publications
Enhancing the accuracy of gender data: Cognitive testing of wording associated with supervisory care
Enhancing the accuracy of gender data: Cognitive testing of wording associated with supervisory care


This publication showcases the results of a qualitative study aimed at cognitively testing wording associated with the time spent on supervisory care. This research roots and builds upon Professor Nancy Folbre’s paper Quantifying Care: Design and Harmonization Issues in Time-Use Surveys and her long-lasting intellectual contribution to the field of care data.

UN Women led this study, in collaboration with the Centre of Excellence on Gender Statistics (CEGS) in Mexico and El Colegio de Mexico, with results presented and discussed during a webinar in July 2022. The ultimate aim of this study is to contribute to the ongoing international efforts to improve survey methods for time-use statistics and more specifically, the accuracy of gender data on unpaid care work.

show filters hide filters

Explore the Data

Learn more about our data resources, why data is missing, and explore our multiple data dashboards to learn more about gender statistics.