Domestic violence is not a predictor of mass murder
The gun-pointing has predictably shifted to finger-pointing since the Texas church shooting. The gunman’s violent past was especially telling for experts on domestic violence.
Deborah Epstein, co-director of the Domestic Violence Clinic at the Georgetown University Law Center, claimed on the PBS NewsHour that there’s a strong correlation between domestic violence and mass shootings. A San Antonio Express-News headline read, “Are mass killings and domestic violence linked? It depends who you ask.” You’d think such a determination would be a matter of fact, not opinion.
Susan Higginbotham, executive director of the Pennsylvania Coalition Against Domestic Violence, said there was “an obvious link.” She at least cited her evidence, a study by Everytown for Gun Safety that she said showed “54% of the perpetrators of these horrific mass killings had a history of domestic or family violence.” But she misconstrued the most important point.
The Everytown study did find that 54% of mass shootings involved intimate partners or family members as victims — but the perpetrators did not necessarily have a history of domestic violence.
Everytown’s case summaries of 156 shootings from 2009 through 2016 reveal 85 incidents in which a gunman murdered at least some current or former intimate partners or family members. Of these, 41% were preceded by other acts of domestic violence. Among the entire pool of mass shootings, only 25% revealed any indication of prior domestic violence.
According to estimates reported by the National Coalition Against Domestic Violence, there are at least 10 million incidents of domestic violence every year. By contrast, there are, on average, about 22 mass shootings annually with at least four fatalities. Were we to predict mass murder on this basis of domestic violence, we would be wrong well more than 99% of the time.
To be clear, domestic violence should never be ignored or taken lightly, and I applaud those trying to prevent it. But please don’t diminish your credibility by abusing the data to make your case.