‘Whisper Networks’ Thrive When Women Lose Faith In Formal Systems Of Reporting Sexual Harassment
Image via WFUVThe big idea
Whisper networks – informal channels that women use to warn others about sexual harassment, abuse or assault – take root because formal reporting systems can re-traumatize people who have been harmed. That’s what I found while conducting research on this topic for my dissertation.
These networks form when women are determined to protect each other once they learn of misconduct, because their experience has shown them that formally reporting incidents is slow and generally doesn’t work.
I conducted 20 in-depth and anonymous interviews with women who used whisper networks. I located them directly or indirectly through social media using snowball sampling, a technique that’s useful for finding people who are willing to anonymously share detailed information with researchers.
The women I interviewed were 18 to 64 years old, with almost half from 35 to 44. Most were white, highly educated and either married or in domestic partnerships. A majority were full-time employees, but others were self-employed, worked part time or were students. Their professions and incomes ranged widely.
“There have just been so many grievous abuses in the nine years I’ve been a graduate student,” said Gloria, one of the women I interviewed. “Every single time I have told someone at the university about the professor who assaulted me … the university made the situation worse.”
Claire, a tenured professor at another university, said that after she formally reported the multiple instances of sexual harassment from a co-worker, the perpetrator gained access to the report. “Immediately he starts calling me. Because he can; it’s legal,” Claire said. “It was very traumatizing.”
Jessie, who works as a bartender, described how her co-worker was assaulted in a back cooler. “The guy like came in and just like cornered her and kissed her straight on the lips,” Jessie said. “He was fired, but after six months he got hired back in the same position.”
Her managers explained that they didn’t want to train someone new. Jessie’s co-worker quit, but Jessie, like Gloria and Claire, used a whisper network. In her case, it was to spread the word to other women to protect them from future traumatic encounters with this man.
Why it matters
More than 1 in 3 U.S. women say they have experienced unwanted and inappropriate sexual advances from male co-workers. And yet officially reporting sexual harassment incidents can harm people who file complaints, instead of their perpetrators.
If these reports aren’t ignored altogether, women who file them can end up having their morals questioned or their reputations sullied. They may face retaliation, such as getting demoted.
Sexual harassment targets can become discredited for supposedly leading someone on or seeking attention, or for being deemed overly sensitive, while the harassment goes uninvestigated.
The movie “She Said,” released in October 2022, underscores the limits of whisper networks. It recounts the experiences of two New York Times reporters as they investigated the many cases of abuse perpetuated by Harvey Weinstein – a movie producer and convicted rapist.
Before reports of Weinstein’s abuses emerged in 2017, amplifying the #MeToo movement, rumors about them were reportedly an “open secret” in show business. Although widely known, they weren’t discussed openly.
What’s next
I’m now researching how well whisper networks serve LGBTQ women, women of color and women with disabilities as opposed to straight white women without disabilities.
There’s an unspoken expectation when people share information through whisper networks that listeners will only share the information with others whom they trust.
As a result, LGBTQ women, those who do not fit into gender expectations and women of color may be left out. In addition, neurodivergent women, such as those with autism and attention-deficit/hyperactivity disorder, may be excluded from whisper networks because information is often shared using indirect or nonliteral language.
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