The belief that guns deter crime and support for capital punishment

Abstract

One of the many reasons for gun ownership in the USA is the belief that citizen gun ownership helps to reduce crime. The rationale for this belief can be linked to deterrence – the perception that the threat of harm from confronting someone with a gun outweighs the potential benefit from crime – and will reduce the likelihood of engaging in criminal behavior. Similarly, deterrence is often referenced as a reason to support capital punishment. This is the first study to explicitly link support for the individual threat of lethal violence and the state threat of lethal violence by testing the hypothesis that the belief that guns reduce crime is positively correlated with support for capital punishment. Tests using a 2010 survey support this hypothesis for general support of capital punishment and for support of capital punishment with the life without parole option. The theoretical implications of considering deterrence as a value-expressive argument are explored.

Keywords:

• captial punishment
• guns
• public opinion
• death penalty
• deterrence

View correction statement:

The belief that guns deter crime and support for capital punishment

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. The Violent Crime Control and Law Enforcement Act of 1994 is comprised of several subsections including, the Federal Assault Weapons Ban, and the Federal Death Penalty Act.

2. It should be noted that the United Nations Office on Drug and Crime study does not include data from Russia, China, and Afghanistan.

3. The countries with the highest rates of homicide by firearms included Honduras, El Salvador, and Jamaica (Small Arms Survey, 2007; UNODC, 2012).

4. Maggard et al. (2012) suggest that comparing the sample to the population demographics provides a good check for possible problems with the representativeness of a sample when the response rate is low.

5. The means are reported rather than percentages for nominal variables because each of these variables has been dummy coded to place them on a ratio scale of 0–1 for inclusion in logistic regression models.