OCSE-PISA data provide a story-telling about the different school performances of adolescents girls and boys in STEM disciplines. From the latest She Figures data, progresses are measured on gender equality in research and innovation, though there is still a long way to go. Stories about women in science and technology, as published in magazines and social networks, are often soaked in bold and subtle stereotypes.
A number of complex questions are induced from these observations: Are they generated by society-driven stereotypes and discriminations, and in science too, that proceeds with quantitative measurements and fact checking? What do such stereotypes imply and why is their removal important?
However, a look at facts with a magnifying glass unveils otherwise hidden details, so that we are led to ask: are we looking at the useful observations and asking the useful questions? Is there a women-way in science? Why are we urgently asking all these (important) questions now?
I will elaborate on this, after combining the transformative powers of scientific thinking and of the Labodif School on symbolic male-female difference. While reformulating optimal queries and crumbling the complex questions into simpler pieces, a shift of paradigm will emerge from what-to-do to foster a society transformation, to how-to-do it. And the way we look at reality will never be like before.