Abstract
Objectives
This research examines whether the information about different wrongful conviction rates would affect death penalty opinion. It is the first experiment to examine how different estimates of the rate of wrongful conviction, rather than general information of innocence, affect views about capital punishment.
Methods
I use Amazon Mechanical Turk to conduct the survey experiment. Five hundred two respondents were randomized into different groups to receive different information about wrongful conviction rate.
Results
People who were informed of a wrongful conviction rate of 4.1% were significantly less likely to support the death penalty compared to people who were told no information of the wrongful conviction rate. But knowing a wrongful conviction rate of 1% did not affect people’s death penalty support.
Conclusions
Information about different wrongful conviction rates had different effects on death penalty support. An accurate estimate of the wrongful conviction rate plays an important role in altering death penalty opinion.
Notes
See: Furman v. Georgia, 408 U.S. 238, 92 S. Ct. 2726, 33 L. Ed. 2d 346, 1972b, pp.364. “But, if this information needs supplementing, I believe that the following facts would serve to convince even the most hesitant of citizens to condemn death as a sanction: capital punishment is imposed discriminatorily against certain identifiable classes of people; there is evidence that innocent people have been executed before their innocence can be proved; and the death penalty wreaks havoc with our entire criminal justice system.”
Respondents were told that some percentage of people who were convicted of murder were actually innocent. Not all murders are punishable by the death penalty. Here, I use wrongful conviction rates in murder as a proxy for the wrongful conviction rates in capital cases to reduce the cognitive burden for respondents.
The variance inflation factor (VIF) and the condition index were used to assess multicollinearity among the covariates. None of the variables had a VIF higher than 2, indicating no concern of collinearity. A collinearity problem is indicated when a condition index above the threshold value (30 was used here) accounts for a substantial proportion of variance for two or more coefficients. There was one condition index above the threshold value, and there was only one coefficient associated with it. Therefore, the condition indices raised no concern of collinearity.
Different people may interpret the rates provided in different ways. The question wording did not label these wrongful conviction rates as high or low, unacceptable, or acceptable, allowing respondents to interpret these rates in their own ways.
Given this is an “age of information,” it is possible that the respondents may be aware of the wrongful conviction rate. The national polls and the survey results in the current study both indicate the general public did not know the rate without researcher informing them and tended to greatly overestimate the wrongful conviction rate. For example, the average estimated wrongful conviction rates from national polls were between 10 and 12% (Louis Harris & Associates, 1999; Gallup Organization, 2000, 2003, 2005), far higher than the scholarly estimated rates. The survey used in the current study contains a question asking people’s perception of wrongful conviction rate (“In this country, out of every 100 people convicted of murder, about how many do you think are actually INNOCENT?”) before the treatment and the death penalty question. The average response was 27.1%, again far higher than the scholarly estimated rates. The responses of the control group did not differ from those of other groups. The respondents’ estimates did not affect their death penalty support. The differences between their estimation and the experiment manipulation also did not affect their death penalty support.
0.027% is an estimated wrongful conviction rate in felony cases according to Justice Scalia. I borrowed it here to represent a very low (close to 0) wrongful conviction rate for murder cases.
I reestimated the models using ordered logistic regression (Model 2.2 in Table S2) and multinomial logistic regression (Model 2.3 in Table S2) and got similar results. Though the p values and significance were slightly different from the main model, the direction and the size of the effects were similar.
I reestimated the models using multiple imputation (m = 10) at the item level and got similar results (Model 2.4 in Table S2). Though the p value and significance were slightly different from the main model, the direction and the size of the effect were similar.
Bivariate logistic regression (Table S1 in the Supplementary) yielded an identical result (the likelihood chi-square test statistic = 3.51, p = 0.3189). Compared to the main model with control variables (Table 2), the coefficients in the bivariate model slightly decreased but were still similar in size. The coefficient for the group exposed to a wrongful conviction rate of 4.1% was not significant at the 0.05 level but was significant at the 0.1 level (p = 0.075).
Supplementary analysis (Model 2.1 in Table S2) reports the same regression analysis for respondents who passed the attention check. The direction and size of the effects of key independent variables were similar to the main model.
Standardized coefficients indicate that empathy for criminals and racial resentment were the strongest predictors of death penalty support.
References
Bedau, H. A., & Radelet, M. L. (1987). Miscarriages of justice in potentially capital cases. Stanford Law Review, 40(1), 21. https://doi.org/10.2307/1228828.
Blecker, R. (2013). The death of punishment searching for justice among the worst of the worst. Palgrave Macmillan.
Bohm, R. M. (1989). The effects of classroom instruction and discussion on death penalty opinions: A teaching note. Journal of Criminal Justice, 17(2), 123–131. https://doi.org/10.1016/0047-2352(89)90005-6.
Bohm, R. M. (1990). Death penalty opinions: A classroom experience and public commitment. Sociological Inquiry, 60(3), 285–297. https://doi.org/10.1111/j.1475-682X.1990.tb00146.x.
Bohm, R. M., & Vogel, R. E. (1991). Educational experiences and death penalty opinions: Stimuli that produce changes. Journal of Criminal Justice Education, 2(1), 69–80. https://doi.org/10.1080/10511259100082291.
Bohm, R. M., & Vogel, R. E. (1994). A comparison of factors associated with uninformed and informed death penalty opinions. Journal of Criminal Justice, 22(2), 125–143. https://doi.org/10.1016/0047-2352(94)90108-2.
Bohm, R. M., & Vogel, B. L. (2004). More than ten years after: The long-term stability of informed death penalty opinions. Journal of Criminal Justice, 32(4), 307–327. https://doi.org/10.1016/j.jcrimjus.2004.04.003.
Bohm, R. M., Clark, L. J., & Aveni, A. F. (1991). Knowledge and death penalty opinion: A test of the Marshall hypotheses. Journal of Research in Crime and Delinquency, 28(3), 360–387. https://doi.org/10.1177/0022427891028003006.
Bohm, R. M., Vogel, R. E., & Maisto, A. A. (1993). Knowledge and death penalty opinion: A panel study. Journal of Criminal Justice, 21(1), 29–45. https://doi.org/10.1016/0047-2352(93)90004-7.
Cassell, P. G. (2018). Overstating America’s wrongful conviction rate? Reassessing the conventional wisdom about the prevalence of wrongful convictions. Arizona Law Review, 60, 815–863. https://doi.org/10.2139/ssrn.3276185.
Clarke, A., Lambert, E., & Whitt, L. A. (2001). Executing the innocent: The next step in the Marshall hypotheses. New York University Review of Law & Social Change, 26(3), 309–346.
Cochran, J. K., & Chamlin, M. B. (2005). Can information change public opinion? Another test of the Marshall hypotheses. Journal of Criminal Justice, 33(6), 573–584. https://doi.org/10.1016/j.jcrimjus.2005.08.006.
Cox, A. K. (2013). Student death penalty attitudes: Does new information matter? Journal of Criminal Justice Education, 24(4), 443–460. https://doi.org/10.1080/10511253.2013.787638.
Enns, P. K. (2016). Explaining the public’s punitiveness. In Incarceration Nation (pp. 74–99). Cambridge University Press. https://doi.org/10.1017/CBO9781316471029.004.
Furman v. Georgia. (1972). 408 U.S. 238, 92 S. Ct. 2726, 33 L. Ed. 2d 346
Gallup Organization. (2000). Gallup news service poll: Past presidents/internet, question 58 [USGALLUP.022400.R4]. Gallup Organization. Roper Center for Public Opinion Research.
Gallup Organization. (2003). Gallup organization poll: May 2003, Question 49 [USGALLUP.03M005.R23]. Gallup Organization. Roper Center for Public Opinion Research.
Gallup Organization. (2005). Gallup organization poll: May 2005, question 75 [USGALLUP.05MA0002.R24]. Gallup Organization. Roper Center for Public Opinion Research.
Gross, S. R., O’Brien, B., Hu, C., & Kennedy, E. H. (2014). Rate of false conviction of criminal defendants who are sentenced to death. Proceedings of the National Academy of Sciences, 111(20), 7230–7235. https://doi.org/10.1073/pnas.1306417111.
Kennedy-Kollar, D., & Mandery, E. J. (2010). Testing the Marshall hypothesis and its antithesis: the effect of biased information on death-penalty opinion. Criminal Justice Studies, 23(1), 65–83. https://doi.org/10.1080/14786011003634480.
Lambert, E., & Clarke, A. (2001). The impact of information on an individual’s support of the death penalty: A partial test of the Marshall hypothesis among college students. Criminal Justice Policy Review, 12(3), 215–234. https://doi.org/10.1177/0887403401012003003.
Lambert, E. G., Camp, S. D., Clarke, A., & Jiang, S. (2011). The impact of information on death penalty support, revisited. Crime & Delinquency, 57(4), 572–599. https://doi.org/10.1177/0011128707312147.
Lee, G. M., Bohm, R. M., & Pazzani, L. M. (2014). Knowledge and death penalty opinion: The Marshall hypotheses revisited. American Journal of Criminal Justice, 39(3), 642–659. https://doi.org/10.1007/s12103-013-9229-z.
Liptak, A. (2008). Consensus on counting the innocent: We can’t. The New York Times https://www.nytimes.com/2008/03/25/us/25bar.html.
Lord, C. G., Ross, L., & Lepper, M. R. (1979). Biased assimilation and attitude polarization: The effects of prior theories on subsequently considered evidence. Journal of Personality and Social Psychology, 37(11), 2098–2109. https://doi.org/10.1037/0022-3514.37.11.
Louis Harris & Associates. (1999). Louis Harris & Associates Poll: July 1999, Question 5 [USHARRIS.072899.R5]. Louis Harris & Associates. Cornell University, Ithaca, NY: Roper Center for Public Opinion Research.
Markman, S. J., & Cassell, P. G. (1988). Protecting the innocent: A response to the Bedau-Radelet study. Stanford Law Review, 41(1), 121. https://doi.org/10.2307/1228837.
Kansas v. Marsh. (2006), 548 U.S. 163, 126 S. Ct. 2516, 165 L. Ed. 2d 429
Marshall, L. C. (2004). The innocence revolution and the death penalty. Ohio State Journal of Criminal Law, 1, 1573–1584.
Michel, C., & Cochran, J. K. (2011). The effects of information on change in death penalty support: race- and gender-specific extensions of the Marshall hypotheses. Journal of Ethnicity in Criminal Justice, 9(4), 291–313. https://doi.org/10.1080/15377938.2011.609430.
Mitchell, A. D. (2006). The effect of the Marshall hypothesis on attitudes toward the death penalty. Race, gender & class, 13(1–2), 221–247.
Mullinix, K. J., Leeper, T. J., Druckman, J. N., & Freese, J. (2015). The generalizability of survey experiments. Journal of Experimental Political Science, 2(2), 109–138. https://doi.org/10.1017/XPS.2015.19.
Norris, R. J., & Mullinix, K. J. (2019). Framing innocence: An experimental test of the effects of wrongful convictions on public opinion. Journal of Experimental Criminology. https://doi.org/10.1007/s11292-019-09360-7.
Peffley, M., & Hurwitz, J. (2007). Persuasion and resistance: Race and the death penalty in America. American Journal of Political Science, 51(4), 996–1012. https://doi.org/10.1111/j.1540-5907.2007.00293.x.
Redlawsk, D. P., Civettini, A. J. W., & Emmerson, K. M. (2010). The affective tipping point: Do motivated reasoners ever “get it”? Political Psychology, 31(4), 563–593. https://doi.org/10.1111/j.1467-9221.2010.00772.x.
Risinger, D. M. (2007). Innocents convicted: An empirical justified factual wrongful conviction rate. Journal of Criminal Law and Criminology, 97(3), 761–806.
Sandys, M. (1995). Attitudinal change among students in a capital punishment class: It may be possible. American Journal of Criminal Justice, 20(1), 37–55. https://doi.org/10.1007/BF02886117.
Sarat, A., & Vidmar, N. (1976). Public opinion, the death penalty, and the eighth amendment: Testing the Marshall Hypothesis. Wisconsin Law Review, 171–206.
Simons, D. J., & Chabris, C. F. (2012). Common (mis)beliefs about memory: A replication and comparison of telephone and Mechanical Turk survey methods. PLoS ONE, 7(12), e51876. https://doi.org/10.1371/journal.pone.0051876.
Unnever, J. D., & Cullen, F. T. (2005). Executing the innocent and support for capital punishment: Implications for public policy. Criminology & Public Policy, 4(1), 3–38. https://doi.org/10.1111/j.1745-9133.2005.00002.x.
Vidmar, N., & Dittenhoffer, T. (1981). Informed public opinion and death penalty attitudes. Canadian Journal of Criminology, 23(1), 43–56.
Vidmar, N., & Ellsworth, P. C. (1974). Public opinion and the death penalty. Stanford Law Review, 26, 1245–1270.
Vollum, S., Mallicoat, S. L., & Buffington-Vollum, J. (2009). Death penalty attitudes in an increasingly critical climate: value-expressive support and attitude mutability. The Southwest Journal of Criminal Justice, 5(3), 221–242.
Weinberg, J., Freese, J., & McElhattan, D. (2014). Comparing data characteristics and results of an online factorial survey between a population-based and a crowdsource-recruited sample. Sociological Science, 1, 292–310. https://doi.org/10.15195/v1.a19.
Wright, H. O., Bohm, R. M., & Jamieson, K. M. (1995). A comparison of uninformed and informed death penalty opinions: A replication and expansion. American Journal of Criminal Justice, 20(1), 57–87. https://doi.org/10.1007/BF02886118.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
ESM 1
(DOCX 41 kb)
Rights and permissions
About this article
Cite this article
Wu, S. The effect of wrongful conviction rate on death penalty support: a research note. J Exp Criminol 18, 871–884 (2022). https://doi.org/10.1007/s11292-021-09467-w
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11292-021-09467-w