Survey header Sprint Gender Survey
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Gender Survey

Aligned with EU and WUR policy, our SPRINT project is required to examine and foster its contribution to gender equality in academia and research.

Three objectives for gender equality in research underpin the European Commission's strategy on gender equality in research and innovation policy:

  • Fostering equality in scientific careers;
  • Ensuring gender balance in decision-making processes and bodies;
  • Integrating the gender dimension in research and innovation content,

Within EU projects, such as SPRINT, the major contexts for fostering these objectives are the institutional environment of all partners as well as the design and enactment of the project partnership and collaboration.
To be able to meaningfully foster and monitor the process several activities were included in the GA of the project as a questionnaire in the beginning phase of the project.

Below you find the project’s gender questionnaire asking about your knowledge and perceptions in these three categories so we can

NOW: build a baseline where we stand now
FOLLOW UP with a trajectory for support and possibly training options
REVIEW AT VARIOUS STAGES how we have advanced in the various objectives and adjust strategies where needed
REPORT at the end what has been achieved, what opportunities have been taken and constraints overcome, what we learnt and what recommendations to give to similar projects in the future.

In line with the new guidelines for Horizon Europe, the SPRINT gender team wishes to recognize in its work the heterogeneity among women and among men; it therefore expands the gender focus into its intersection with other socially valued dimensions such as race, ethnicity, class/wealth, age/generation, locality, civic status, health status, sexual orientation. Some call this a gender+ or intersectional approach. This is also why we ask you at the end for some background details to enable us to cross-analyse the findings.

Please be assured that we – in line with the European privacy rules on data – will not expose any detailed findings that would allow individual recognition.

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