Are police agencies less likely to use torture in democracies than in non-democracies? Much empirical research has shown that democracies are less likely to engage in torture in general, but most of this research does not distinguish among victim types or state agencies. Using the Ill-Treatment and Torture (ITT) Data, we focus on police agencies and evaluate whether they are less likely to use torture against (separately) political dissidents, criminals, and marginalized communities. Using logistic regressions with random effects, we find that the well-established and relatively high level of democracies’ respect for the rights of dissidents extends to police agencies as well. However, we find weaker statistical evidence that police agencies in democracies are less likely to use torture against criminals, and no evidence that they are less likely to torture marginalized communities. Our results suggest that one of the most robust empirical facts in the literature must be qualified. The protection from violence offered by democratic institutions does not seem to generalize beyond violence directly related to political competition and dissent.

Data and models To examine torture committed by specific government actors against specific types of victims, we use the ITT country-year data (Conrad et al., 2013), which contains indicators created from content analyses of Amnesty International’s annual reports, press releases, and Action Alerts. The data distinguish between both the state agency accused of abuse and the identity of the victim. Agencies include the police, the military, the paramilitary, prison guards, intelligence services, and immigration detention centers. We use only indicators for which the state agency is designated as “police.”7 Victim types examined here include criminal, dissident, and marginalized individuals, which includes religious and ethnic groups, youths, the elderly, and immigrants (Conrad et al., 2013: 203).8 This allows us to examine police violence against distinct victim types. We focus exclusively on the police because this agency is the most useful for comparing results for repressive and oppressive violence. This is because the distribution of victim types is more even for the police than for other government agencies. According to the ITT data, the police are the most likely agency to be accused of torturing dissidents and marginalized groups, and are the second most likely (after prison staff) to be accused of torturing criminals. Intelligence services and the military are unlikely to have access to criminal suspects, resulting in few allegations of torture targeting this group, while prison staff are relatively unlikely to be accused of torturing members of marginalized groups. ITT’s torture variables are ordinal scales ranging from 0 to 5, with higher values indicating allegations of more systematic/widespread torture. It should be noted that ITT’s country-year data record allegations of torture that occur throughout the entire country. This results in a preponderance of zeroes (no alleged torture) and few observations in higher categories. Because of this, we transform these ordinal measures into dichotomous ones.9 In the online appendix we show results for ordered response and linear models. Our substantive results do not change. In the first set of models, we examine the effect of competition on police torture against political dissidents. Violence against dissident groups is commonly the focus of human rights studies, and in these models we seek to establish whether the negative association between competition and the repression of dissidents extends to police torture that targets other groups. In the second set of models, we examine whether judicial constraints have an effect on police torture. We use three indicators of competition in our analyses, and three indicators of judicial independence/effectiveness. Using several variables helps to protect against one dataset driving our results, and using two categories of measures—political competition and executive constraints—allows us to analyze two distinct features of democracy. For the competition measures, we first use the Polyarchy variable from the Varieties of Democracy (V Dem) data. Polyarchy is a continuous variable ranging from 0 to 1 and is calculated from a weighted average of measures of freedom of expression, freedom of association, fair elections, an elected executive, and suffrage, and from an interaction between all of these variables (Coppedge et al., 2017). Next, we use Parcomp from the Polity IV data, which is an ordinal measure ranging from 0 to 5, with 5 indicating that changes in governmental policies can be relatively safely pursued. Finally, we use the dichotomous ACLP variable (Alvarez et al., 1996) as recoded and extended by Cheibub et al. (2010). The authors create a dichotomous indicator for whether a country is democratic based on political contestation for executive and legislative offices. Countries that have two or more parties, an elected executive, and an elected legislature (without reverting to non-competitive political practices) are classified as democracies. For the executive constraints measures, we first use the V Dem measure of judicial constraints, which is a continuous 0-1 scale that is calculated via Bayesian factor analysis of five indicators: executive respect of the constitution, compliance with the judiciary, compliance with the high court, the independence of the high court, and the independence of lower courts (Coppedge et al., 2017). Second, we use the CIRI indicator for judicial independence, which is an ordinal variable ranging from 0 to 2, with higher values indicating a more independent judiciary (Cingranelli et al., 2014). Finally, we use the Polity IV measure of executive constraints, an ordinal measure ranging 1 to 7, with higher levels indicating more institutional constraints on executive decision making, including an effective high court (Marshall and Jaggers, 2009). We use logit models with random effects for country to account for the panel structure of our data. Including these unit-specific effects accounts for unspecified heterogeneity across countries and allows us to draw more reliable inferences. The data cover 147 countries for the years 1995 to 2005 (inclusive). We conduct separate analyses for the three types of victim groups: marginalized communities, dissidents, and criminals. Separate models are also used for each indicator of competition and judicial constraints, for a total of 18 models. In addition to measures of democracy, in each model we include (the natural logs of) GDP/capita and population size from the World Bank. We also include ITT’s measure of restricted access, as suggested in the user’s guide (Conrad and Moore, 2011: 14). This dichotomous variable, Restricted Access, is coded 1 for years in which Amnesty International reports that it, or another INGO, had trouble obtaining access to a detention center.

Results Coefficient estimates Figure 1 shows the results from our models examining the effects of political competition on police torture.10 Point estimates of the coefficients are displayed with associated 90% confidence intervals.11 Coefficient values are displayed along the horizontal axis. Download Open in new tab Download in PowerPoint Our results suggest a negative association between democracy and the torture of dissidents. All three measures of democracy are associated with a statistically significant decrease in the likelihood that police agencies use torture to any extent. The results of these models suggest that the relationship between democracy and the torture of political dissidents extends to police agencies. When we look at other victim types, however, we find weaker evidence that democracies have higher respect than autocracies, on average, for the human rights of these victim types. Although our analyses of police–criminal torture shows a negative relationship between democracy and torture, the estimates are significant at the α = 0 . 10 level in one of the three models. Polyarchy has a negative and significant relationship with the probability of torture by police agencies, while Parcomp and ACLP show negative but insignificant relationships with police torture against criminals. With respect to the police–marginalized communities analyses, none of the measures of democracy have a statistically significant association with torture by police agencies, all of the estimates are close to zero, and one is actually positive. Given the usual finding that democracies are less likely to engage in torture than non-democracies, these null results are interesting. When we look beyond political dissidents, we find weaker evidence that police agencies in democracies are less likely to use torture. Figure 2 shows the results from our models examining the effect of executive constraints on democracies. As with political competition, all three measures of judicial constraints show a negative and significant relationship with police torture of political dissidents. Download Open in new tab Download in PowerPoint In the police–criminal models, we find mixed results. Judicial constraints and executive constraints have a negative and significant relationship with the likelihood that police agencies torture, while CIRI is insignificant. Across all six models of police–criminal torture, half of the measures—parcomp, ACLP, and CIRI—produce no significant effect on the likelihood of police torture. Finally, in the police–marginalized communities models, we again cannot reject the null hypothesis that democracy has no effect on the use of torture by police. Surprisingly, all three models return positive coefficients, although judicial constraints and executive constraints are close to zero. These results mimic the results of the police–marginalized communities models with the competition measures; across all six police–marginalized models, we fail to find statistical significance with respect to democracy and the use of torture. Further evaluation of null results In order to more thoroughly evaluate our null results, we perform the confidence interval version of the two one-sided test (TOST) proposed by Rainey (2014). Rainey argues that demonstrating a negligible effect requires more than statistically insignificant results. Rather, researchers should demonstrate that the estimated sampling distribution of their quantity of interest does not contain values that would constitute a meaningful effect. This requires that we choose a threshold for a “meaningful effect.” Since the ITT data have not been extensively analyzed, it is unclear how to define a meaningful effect, so we proceed as follows: for each model that produced a null result we simulate 10 000 draws from a multivariate normal distribution using the estimated coefficients and covariance matrices. We calculate a baseline probability by setting the values of the control variables to their means (the natural logs of GDP per capita and population) or modes (restricted access), and setting each competition or judicial constraints variable at a typical value.12 This resulted in 10 000 predicted probabilities for each model, and we used the mean probability as the baseline. We then changed the value of each variable of interest to its maximum and calculated the mean change in the probability from the baseline, with a 90% confidence interval. The lower bound of each confidence interval serves as the maximum plausible reduction in the probability of torture that results from changing each indicator from a typical to a high value. Tables 1 and 2 show, for each model, the baseline probability of torture, the maximum plausible reduction, and this reduction expressed as a percentage of the baseline. We calculate percentage reductions since the baseline probability is different in each case, and in some cases is low enough to preclude a large absolute reduction. The ITT country-year data measures allegations of torture that implicate state agents across the entire country, which are rare, so for all models the baseline probability is low. The larger the absolute values in columns 2 and 3 of each table, the larger the range of threshold values for which we can not rule out a meaningful effect. Thus the evidence for a negligible effect is stronger for marginalized groups than for criminals. Table 1. TOST for Competition Variables. View larger version Table 2. TOST for Judicial Variables. View larger version

Conclusion There is a broad consensus among political scientists that democratic political competition and governmental constraints on the executive reduce state violence. The analyses on which this consensus is based do not typically distinguish between violence that targets opposition groups and violence that does not. This makes it impossible to determine whether the pacifying effects of these institutions apply equally to the distinct groups that are the most likely targets of violence. Further, since democratic competition necessarily entails a limited amount of violence against peaceful dissidents, it is imperative to draw a distinction between repressive and oppressive violence when conducting such an analysis. We address this issue by employing the recently released ITT country-year data (Conrad et al., 2013), which allows analysts to disaggregate allegations of state violence by the identity of the victim and the agency accused of abuse. With respect to violence perpetrated by the police, we find strong evidence that competition and constraints are negatively associated with torture that targets dissidents. This is consistent with the body of research on which we build, and is unsurprising. We find only mixed evidence that these institutions help reduce torture that targets criminals. Finally, we find no compelling evidence that competition or judicial constraints decrease the use of torture against marginalized groups. In the case of judicial institutions, this is somewhat surprising, as we expected these institutions would prove effective at deterring oppressive violence. Our results suggest that one of the most robust findings in the literature must be qualified: some vulnerable groups do not enjoy the protection created by political competition and strong courts of law. If recent episodes of police violence in democracies are aberrant, it is only because police violence does not typically rise to the level seen in these cases, not because such violence is occurring in democracies.

Acknowledgements We thank Sam Bell, Thorin Wright, Jacqueline DeMeritt, George Williford, Chad Clay, two anonymous reviewers, and the UGA SPIA workshop for their helpful comments and suggestions.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article. Supplementary materials

The supplementary files are available at http://journals.sagepub.com/doi/suppl/10.1177/2053168018759126.

Notes 1.

The Guardian maintains https://www.theguardian.com/us-news/homan-square—a page on their website devoted exclusively to reporting on Homan Square. 2.

https://www.hrw.org/news/2017/09/07/philippine-president-rodrigo-dutertes-war-drugs 3.

https://www.theatlantic.com/international/archive/2017/08/duterte-drug-war/537612/ 4.

https://www.theguardian.com/global-development-professionals-network/2016/aug/03/rio-police-violent-killing-olympics-torture 5.

See, e.g., Davenport (1995); Poe (2004). 6.

See also Vanberg (2005), who argues that effective constitutional courts can help coordinate mass responses to government abuse because their decisions are highly visible. 7.

ITT also categorizes “unknown” perpetrator agencies; we exclude this scale. 8.

ITT also includes State Agent victims, but a lack of non-zero observations for this scale prevents meaningful analysis. We exclude this and the “unknown” victim type scale. 9.

The criminal torture scale, which is the most balanced of the scales, has 82.5% (or 1260 of 1526) observations in the 0 category, less than 1% in the 1 category, 5% 2s, 5% 3s, 4% 4s and 3% 5s. This imbalance prevented reliable estimates of variance-covariance matrices in several ordered response models using the original scales. 10.

Due to space constraints, we omit discussion of the control variable results, but interested readers can find these in the online appendix. 11.

Confidence intervals that overlap with 0 indicate that the coefficient estimate is insignificant at the α = 0 . 10 level (two tailed test). 12.

In the models using the dichotomous ACLP indicator, we set that variable to 0 to calculate the baseline. We used the mode for the Parcomp indicator, and set the Polyarchy variable to its mean. For models with the ordinal CIRI judicial independence scale, we set that variable to its mode. We set Polity’s xconst variable to its median (the mode is the maximum value of 7), and set the V-Dem judicial constraints indicator to its mean.

Carnegie Corporation of New York Grant

This publication was made possible (in part) by a grant from Carnegie Corporation of New York. The statements made and views expressed are solely the responsibility of the author.