Data are not neutral: how female researchers are changing the way we read society

Alongside Saraceno is the work of a new generation of demographers who use international datasets and advanced quantitative methods to interpret social transformations. Alessandra Minello, a researcher at the University of Padua and the Max Planck Institute for demographic research, has studied the impact of the Covid-19 pandemic on the reproductive choices of European couples. Through international surveys, Minello showed how economic uncertainty and difficulties in reconciling work and family life contributed to the drop in births observed in 2020 and 2021 in many European countries. His work showed how behind apparently neutral demographic indicators lie deeply differentiated social effects.

Also in the field of comparative demography is Letizia Mencarini, a professor at Bocconi University and one of Europe's leading scholars of family behaviour and fertility. Mencarini showed, for example, how the division of domestic labour within couples directly influences decisions to have children. In contexts where family work is more evenly distributed, the probability of having a second child is significantly higher according to several European comparative studies.

In the field of labour economics and population ageing, on the other hand, Agar Brugiavini, an economist at the Ca' Foscari University of Venice and one of Europe's leading experts on pension systems, stands out. Brugiavini participated in the development of the international database Share (Survey of health, ageing and retirement in Europe), one of the main European surveys dedicated to the living conditions of the population over 50. In Europe, women over the age of sixty-five have on average pensions that are about thirty per cent lower than men, a difference linked to more discontinuous working careers and lower average wages during working life. Share data also showed that individuals with higher levels of education live up to seven years longer in good health than those with low levels of education, underlining the strong link between socio-economic conditions, health and the quality of ageing.

Alongside academic research, the role of female professionals working in the field of visualisation and data communication has also grown in recent years. Prominent among these is Giorgia Lupi, information designer and co-founder of the international studio Accurat. Her work has helped to redefine the way data is represented visually, demonstrating that visualisation is not just an aesthetic exercise but a tool for interpreting reality. One thinks of his Dear Data project, which also became a book and was realised together with US designer Stefanie Posavec. For a year, they exchanged weekly hand-drawn postcards representing data collected on their daily lives, from social interactions to emotions or daily habits. The project demonstrated how even small personal datasets can be transformed into visual narratives capable of making data more human, understandable and accessible to the public.

An important contribution to the dissemination of data culture also comes from the work of Donata Columbro, journalist and data humanizer. In her work she analyses feminicides, migration and social inequalities, highlighting the importance of looking at data over time through so-called 'time series'. For example, in Italia 97 women were murdered in 2025, compared to 118 in 2024 and 120 in 2023, with most cases still occurring in the family or emotional sphere. Without comparing this data with previous years, the phenomenon may seem isolated, whereas time series show that gender-based violence is a structural and persistent fact. Columbro's work thus demonstrates how the interpretation of data, considering trends over time and context, can correct distorted perceptions, influence public debate, and guide more informed policies.

In the field of methodological statistics, however, figures such as Monica Pratesi, professor of economic statistics at the University of Pisa and former president of the Italian Statistical Society, have emerged. She has distinguished herself for the development of advanced statistical methods, in particular Small Area Estimation techniques, which allow the estimation of poverty indicators and living conditions at a very detailed territorial level, such as provinces or municipalities. These models make it possible to identify the most vulnerable areas more precisely and to target public policies. They have been used to map the distribution of educational poverty and territorial inequalities in Italia.

In the field of gender medicine, the figure of Flavia Franconi, a pharmacologist specialising in the analysis of sex-disaggregated clinical data, emerges, showing how drugs and therapies can have different effects on men and women. Her work highlighted, for example, how many traditional clinical trials have historically used dominantly male samples, producing gaps in knowledge about the effects of drugs on women.

What emerges from all the contributions of these scholars is that it is not just a matter of adding women to the data, but of transforming the way the data itself is conceived and interpreted. Every dataset, every indicator, every predictive model carries with it implicit assumptions about the world: what we choose to measure, how we measure it and which categories are taken into account decisively determine the conclusions we can draw. The Italian researchers mentioned above have shown that applying a more diversified perspective means making phenomena visible that would otherwise remain marginal. In this sense, the female presence in the production of data enriches the entire scientific narrative. It not only amplifies neglected voices, but also changes the very way in which society makes decisions. Data, thus redefined, become instruments of empowerment for the entire community, because they make reality fairer and more open to evidence-based solutions.