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Women at Work: Sexual Harassment

Resource Type
  • Keplinger, Ksenia
Publication Date
  • Abstract

    Over the last two years, awareness about the sexual mistreatment of women has stunned the world. According to analysis by the New York Times, the defeat of Hilary Clinton and election of Donald Trump spurred a women’s movement in the US that began in November of 2016 and resulted in protests across the country, including the largest single-day protest in history on January 21, 2017. Later that year, the #MeToo movement (starting in October 2017) and subsequent #TimesUp movement (starting in January 2018) galvanized women to unite against sexual assault and sexual harassment, which has become the hallmark of the current women’s movement. But has anything changed over this time period in regard to the sexual harassment of women? We examine data from over 500 women at two points in time (September 2016 and September 2018) and found reduced levels of the most egregious forms of sexual harassment (unwanted sexual attention and sexual coercion) but increased levels of gender harassment in 2018 compared to data collected in 2016. More importantly, sexual harassment had a weaker relationship with women’s negative self-views (lower self-esteem, higher self-doubt) in 2018 compared to 2016. Qualitative interviews collected from women in the fall of 2016 and in the fall of 2018 from the same women, support the quantitative data. They suggest that the decrease in the more egregious forms of sexual harassment is due to the increased scrutiny on the topic and the increase in gender harassment is the result of backlash against women. The interviewees also suggest that the diminished relationship between sexual harassment and negative self-views was the result of reduced shame and increased support and empowerment.

Update Metadata: 2019-05-07 | Issue Number: 1 | Registration Date: 2019-05-07

Keplinger, Ksenia (2019): Women at Work: Sexual Harassment. Version: 2. ICPSR - Interuniversity Consortium for Political and Social Research. Dataset.