Stand your ground: Using import.io to analyze race and gender bias in Florida assault cases

Is there statistical evidence of race and gender bias in the enforcement of Stand Your Ground (SYG) laws in the United States?

SYG laws – in operation across most US states – state that a citizen may use any level of force, including lethal, if he or she reasonably perceive an immediate threat of bodily harm or death. Florida passed the first such law in 2005.

Justin Murphy, Assistant Professor (Lecturer) at Southampton University, recently shared a paper where he used import.io and data from the Tampa Bay Times to argue that: “’Stand your ground’ laws reinforce white supremacy in the streets and patriarchy in the home”. You can read Justin’s blog post (which we’ve posted a summary of below) here and his paper in full here.

The two key findings

  1. The probability of conviction for a white defendant against a white victim in a typical case is fairly high at around 90% but with a large margin of error, whereas the probability of conviction for a black defendant against a white victim approaches 100%, even after controlling for more than 10 different objective factors related to the circumstances of the incident.
  2. The probability of conviction for a male defendant in a typical domestic case is found to be about 40%, but for a female defendant in an otherwise objectively equivalent case the probability of conviction increases dramatically to 80%.

What these models teach us about recent cases

  1. The probability George Zimmerman was going to be found guilty of murdering unarmed black teenager Trayvon Martin in 2012 was marginally greater than 50% but would have been about 98% if Trayvon Martin had been white.
  2. Black female Marissa Alexander who fired a physically innocuous warning shot to deter her husband in 2010 faced a probability of conviction marginally greater than 50%, but the probability of conviction for a male defendant in an otherwise objectively equivalent situation would have been around only 12%.

Thanks to Justin for reaching out to share his findings. If you’ve created or heard of any interesting uses of import.io, or any examples of how data can shape our view of the world around us, send us an email to hello@import.io.

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