Publikationen

Autor	Gerber, Nina; Stöver, Alina; Mayer, Peter
Datum	2024
Art	Conference Proceedings
Abstrakt	Gender imbalances are prevalent in computer science and the security and privacy (S&P) field in particular, giving rise to gender stereotypes. The existence of such stereotypes might elicit the stereotype threat effect well-known from research in math settings: mere exposure to stereotypes can decrease the performance in and attitude towards specific fields. In this work, we investigate whether the stereotype threat effect influences women and men in the S&P field. We conducted an online experiment with multiple groups to explore whether videos that depict and counteract gender stereotypes influence S&P attitudes and intentions (RQ1), and (self-assessed) S&P knowledge (RQ2). We find overall little evidence for the stereotype threat effect, but our results show that women in the condition actively counteracting gender stereotypes report a higher interest in preventing hacker access to their devices than women in the stereotype conditions. In addition, we find that men score higher than women in a variety of self-report measures, except for security and privacy concerns. These results indicate that stereotypes might need to be addressed early on to prevent stereotypes from becoming social norms and a self-fulfilling prophecy of gender imbalance in the S&P field.
Konferenz	Symposium on Usable Privacy and Security (SOUPS 2024)
ISBN	978-1-939133-42-7
In	Twentieth Symposium on Usable Privacy and Security (SOUPS 2024), p.547-566
Publisher	USENIX Association
Url	https://tubiblio.ulb.tu-darmstadt.de/id/eprint/149940