Article Accountability by Numbers: A New Global Transitional Justice Dataset (1946-2016) Genevieve Bates, Ipek Cinar, and Monika Nalepa In an era of democratic backsliding, scholars and policymakers wonder if failure to reckon with former authoritarian elites and their collaborators plays a role. Yet without adequate data on the way former autocracies and countries emerging from conflict deal with human rights violators, it is hard to tell if new democracies are unstable because of their failure to reckon with their former authoritarian elites or despite it. We introduce a dataset of personnel transitional justice events that allows scholars to answer such questions, disaggregating these events temporally from the date of a country's democratization. The time series nature of our data allows scholars to measure key characteristics of states' dealing with their past and complements existing transitional justice datasets by focusing not only on post-conflict societies and not only on post-authoritarian societies, but on both. To showcase the possibilities our data affords scholars, we use it to develop three novel measures of personnel transitional justice: severity, urgency, and volatility. The granular structure of our data allows researchers to construct additional measures depending on their theoretical questions of interest. We illustrate the use of severity of transitional justice in a regression that also employs data from the Varieties of Democracy project. We live in an era of democratic backsliding: fragile new democracies are at risk of reverting back to dictatorship. To see examples of this, one need look no further than Poland, Hungary, Turkey, and Venezuela (Bermeo 2016, Lust and Waldner 2015, Serra 2012). Can transitional justice—that is, mechanisms set up by new democracies to deal with former authoritarian elites—prevent such backsliding from happening? Or is backsliding occurring despite transitional justice provi- sions? To answer these kinds of questions, scholars need to have access to temporally organized data on how states deal with outgoing autocrats, their collaborators, and perpetrators of human rights violations. We introduce such a dataset in a comprehensive and theoretically motivated way. Transitional justice (TJ) refers to the "formal and informal procedures implemented by a group or institution of accepted legitimacy around the time of transition A list of permanent links to Supplemental Materials provided by the authors precedes the References section. *Data replication sets are available in HarvardDataverse at: https://doi.org/10.79W/DVN/lHCPSG Genevieve Bates is a Doctoral Candidate in Comparative Politics at the University of Chicago. Her research interests include political violence, post-conflict politics, and transitional justice (genbates@uchicago.edu). Her research focuses on the International Criminal Court, exploring how ICC investigations affect local-level politics and decision-making in the countries where Court involvement is a threat. Ipek Cinar is a Doctoral Student in Comparative Politics at the University of Chicago (ipekcinar@uchicago.edu). Her research interests include political parties and democracy, authoritarianism and political economy of regime transitions. Monika Nalepa © is Associate Professor of Political Science and a Professor in the College at the University of Chicago (mnalepa@uchicago. edu). With a focus on post-communist Europe, her research interests include transitional justice, parties and legislatures, and game-theoretic approaches to comparative politics. Her first book, Skeletons in the Closet: Transitional Justice in Post-Communist Europe (2010), was published in the Cambridge Studies in Comparative Politics Series and received the Best Book award from the Comparative Democratization section of the American Political Science Association and the leon Epstein Outstanding Book Award from the Political Organizations and Parties section ofAPSA. She has published her research in the Journal of Comparative Politics, World Politics, Journal of Conflict Resolution, Journal of Theoretical Politics, Studies in Grammar, Logic and Rhetoric, - R') t - Tmt 2016 or end of democratic spell miti(P' - R') Regressive Events swing. We want our volatility measure to increase when the number of these years is lower. At the same time, because the maximum and minimum net values could be associated with more than a single year in a country's post-transition history, we take the median year of all maximum Figure 6 Volatility of truth commissions application of volatility to the case of truth commissions, has fewer cases than the figures illustrating severity and urgency. Volatility, by far the most complex of the three measures presented here, exposes the potentially greatest problem arising from a coding procedure limited to whether or not a country experienced a personnel transitional justice procedure. First consider the two cases of Lesotho and Nepal, where volatility is very low. These two countries' volatility values approximate situations where transitional justice is implemented once and for all; thus, the coding is not affected by the time at which data were collected. Contrast this with highly volatile countries, such as Liberia, Colombia, and Kenya, where transitional justice is implemented at one point only to be revoked shortly after. In such countries, the coding of the presence or absence of the transitional justice mechanism is highly dependent on the moment in time when the data collection took place. We elaborate on two examples: Lesotho and Kenya. In 2000, Lesotho's government established a Commission of Inquiry to look into the election-related violence of 1998 {Morpheme/Survivor (Maseru) 2000a). While the establishment of the Commission was challenged in court that same year, it ultimately finished its work, releasing a report in October 2001 {Morpheme/The Survivor (Maseru) 2000b, 2002). In Kenya, however, initiatives to establish a permanent truth commission body in the aftermath of the 2002 democratic transition failed alongside the 2005 draft constitution (Human Rights Watch 2008). In Kenya, however, initiatives to establish a permanent truth commission body in the aftermath of the 2002 democratic transition failed alongside the 2005 draft constitution (Human Rights Watch 2008). Years later, in the wake of the 2007-2008 postelection violence, a commission of inquiry (CIPEV and subsequent truth commission were set up to investigate what happened (International Center for Transitional Justice March 2020 | Vol. 18/No. 1 173 Downloaded from https://www.cambridge.org/core. IP address: 86.49.249.113, on 25 Nov 2021 at 16:17:40, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.Org/10.1017/S1 537592719000756 Article Accountability by Numbers 2011). While the CIPEV report was adopted by parliament, the legislative body ultimately sought to censor the Truth, Justice, and Reconciliation Commission report, amending the initial law establishing the body to require implementation of the report only after consideration by parliament (International Center for Transitional Justice 2014). Applying the Measures in a Regression Framework Although the data presented justify our decision to disaggregate personnel transitional justice into events across time and into specific types of mechanisms, we have thus far offered little in terms of links between these events and the replacement of authoritarian elites, which is our motivating question: does reckoning with former authoritarian elites and their collaborators play a role in authoritarian reversals? This section fills the lacuna by applying our data and measures in a regression framework. The power of former authoritarian elites extends beyond the life span of an authoritarian regime. Autocrats may be well positioned to capture state resources at the time of democratic transition, which they can then use in a clientelistic fashion to stay in power (Brun and Diamond 2014; Haggard and Kaufmann 2016; Albertus and Menaldo 2014). The out-going autocrats' access to resources can be cut off if they or their successors are voted out of office following the transition to democracy. Various cases from around the world demonstrate, however, that this removal may only be temporary (Kitschelt et al. 1999). Grzymala-Busse (2002), for instance, attributes the revival of successor authoritarian parties to the organizational advantage authoritarian parties hold over parties that are new to the party system. This organizational advantage allows them to make better use of state resources when they eventually do find themselves in government. Effective personnel transitional justice institutions are often portrayed as the last resort to curb autocrats' unfair advantage. Indeed, scholars of transitional justice have argued that its mechanisms should undercut the privileged position of members or parties of the former autocrats, their collaborators, or their enforcement apparatuses (Stan et al. 2009; David 2011; Vinjamuri and Snyder 2004; Escriba-Folch and Wright 2015). In light of this discussion, personnel transitional justice may plausibly be interpreted as a mechanism preventing former authoritarian elites from holding on to such economic resources. Therefore, a variable measuring the association between economic wealth and political power is an ideal candidate for a dependent variable operation-alizing the effects of transitional justice on the quality of democratic representation. Additionally, given the temporal nature of our data, an ideally suited dependent variable also measures this association over time. Fortunately, the Varieties of Democracy Expert Survey (V-Dem) contains such a measure (Coppedge et al. 2017a). 174 Perspectives on Politics Called "Political Power distributed by Socio-economic status" (PdSES), the variable is based on the following question posed to V-Dem experts: "Is political power distributed according to socioeconomic position?"25 In his clarification note, John Gerring elaborates that the measure was designed to gauge the extent to which inequalities translate into political power (Coppedge et al. 2017b).26 If the goal of personnel transitional justice is to undermine the privileged position of authoritarian elites, this score should increase with the severity of the transitional justice mechanism in question. We present a series of regressions using PdSES as the dependent variable and our measure of severity of the three personnel transitional justice mechanisms—TJ vetting, purges, and truth commissions—as the independent variables. In addition, we make use of the information we collected on timing of democratic transition and on the years lapsed since the transition. To create the dependent variable PdSES, the V-Dem team converted the ordinal expert answers to an interval scale. We truncated the V-Dem panel to match countries and years that occur in our dataset and added measures of transitional justice severity for all three mechanisms. Using OLS is not warranted due to the nested structure of our data, which is a panel containing all the years since the transition for eighty-three countries.27 OLS, due to the homoscedasticity assumption, produces unbiased results only when errors are distributed independently across observations (Raudenbush and Bryk 2002). However, in our case, the errors, like years since transition, are clustered by country. Hence, a multilevel (or mixed) model is the most appropriate. The details of how this multilevel model was developed have been relegated to online appendix A. The results of our regressions are presented in table 2. Model 1 from table 2 is a so-called null model, which only includes the separate error terms for calculating how much of the variation to be explained comes from differences in PdSES within countries instead of between countries. It indicates that 0.81% of the variation is explained by differences between countries. We conclude from this that a hierarchical model is justified in this instance (Finch, Bolin, and Kelley 2014). The next model (2) is a random intercept model that incorporates one explanatory variable at the country level: "years after the transition." We decided to include the variable because TJ vetting severity, like all of our measures of transitional justice, is measured at the country level. Model 3 differs from model 2 only in its error structure. While model 2 admits only random intercepts, model 3 also admits random slopes. In other words, in model 2, only the intercept can vary within countries; the slopes are all constrained to the same country-specific slope. In model 3, both the slopes and intercepts can vary within countries. In model 4, we additionally include the Downloaded from https://www.cambridge.org/core. IP address: 86.49.249.113, on 25 Nov 2021 at 16:17:40, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/! 0.1017/S1 537592719000756 Table 2 Regression results (Dependent variable: Power distributed by socioeconomic status) Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Years after — 0.000 (0.001) -0.009* (0.005) -0.010* (0.005) -0.010** (0.005) -0.009* (0.005) TJ Vetting Sev. — — — 0.665** (0.259) — — Purges Sev. — — — — 0.541 (0.336) — Truth Com Sev. — — — — — 0.117 (0.248) Constant 0.605*** 0.601*** 0.672*** 0.453*** 0.590*** 0.622**** (0.083) (0.084) (0.102) (0.131) (0.113) (0.148) Random Effects: Intercept (Var.) 0.561 0.560 0.837 0.791 0.805 0.856 Years after — — 0.002 0.002 0.002 0.002 (Var.) Residual (Var.) 0.135 0.135 0.070 0.070 0.070 0.070 Observations 1875 1875 1875 1875 1875 1875 Note: *p<0.1, **p<0.05, ***p<0.01 severity of TJ vetting (abbreviated as "TJ Vetting Sev.") as an explanatory variable at the country level. Models 5 and 6 show the results after including the severity of purges and the severity of truth commissions, respectively. In the model that tests the effect of TJ vetting severity, as much as 92% of the variation in the dependent variable is explained by variation between countries as opposed to within countries, again justifying our use of a hierarchical model. The effect of TJ vetting severity of PdSES is quite high (.722), positive, and significant. As higher values of PdSES indicate a weaker correlation between wealth and political status, this is a normatively desirable result. It appears that more severe TJ vetting indeed disentangles economic and political privilege, which are fused under authoritarianism. In contrast, a similarly structured model used for predicting the effect of purges on PdSES (model 5) shows no significant effect of this personnel transitional justice mechanism. The insignificant effect is also smaller —only .56 compared to .722 of TJ vetting severity.28 In the case of truth commission severity (model 6), the effect is still insignificant and, at .108, even smaller. Interestingly, years after transition also has a significant effect on political power distributed by socio-economic status, but the effect is negative. That is, with every year lapsed since the democratic transition, more political power is distributed according to economic wealth and status. The effect, however, is very small. The passage of an additional year lowers the PdSES score only by .01 units on the 5-point scale that measures PdSES. Although this offers some support for our initial hypothesis—one of the personnel transitional justice mechanisms, TJ vetting, weakens the association between economic wealth and political power—the others do not seem to matter. This could be attributed to the fact that our outcome variable is, like vetting, very elite-focused. While Downloaded from https://www.cambridge.org/core. IP address: 86.49.249.113, on 25 Nov 2021 at 16:17:. https://doi.org/! 0.1017/S1 537592719000756 truth commissions and purges can limit the return of former authoritarian elites and perpetrators to positions of power, they both cast a broad net: truth commissions extend their focus beyond elites, and purges rely on the attribution of collective responsibility. In order to dig deeper into the mechanism of TJ vetting—the only significant mechanism within our regression—we perform one more exercise in disaggregation, explained in the next section. Disaggregating Personnel Transitional Justice Further Among elites who sustained the former authoritarian regime are persons whose involvement in it is known, such as high ranking officials of authoritarian parties, and those whose identity is unknown, such as secret police informers, and people who spied on their friends, family, and co-workers. Revealing the truth, and the associated bans on holding public office, can have a different effect in those two cases. In the case of unknown collaborators, if a TJ vetting law is not put in place, politicians who collaborated with the authoritarian regime or committed atrocities in secret can be blackmailed with the threat of revealing these actions by those with credible access to such "skeletons in the closet" (Nalepa 2010b; Ang and Nalepa 2019). Needless to say, if the public still pays attention to what happened in the past, the revelation of such "skeletons" could end a politician's career. In return for their silence, individuals in possession of credible evidence of "skeletons in the closet" can demand rents or policy concessions. Regardless of the currency in which the ransom is paid by the blackmailed politician, the quality of democracy suffers. The mechanism behind the vetting of known collaborators is different. Since getting rid of members who ran the agencies of the former authoritarian regime is similar to getting rid of bureaucrats, one can think of this vetting process as the reverse of a delegation problem. If a newly March 2020 | Vol. 18/No. 1 175 ), subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. Article Accountability by Numbers elected politician comes to office and vets the administrative apparatus so thoroughly that he gets rid of all bureaucrats with policy expertise, he is forced to implement policy in inherently uncertain conditions. Without the expertise of people who ran the agencies under the ancien regime, he cannot know how policy implementation will be affected by states of the world unknown to him. Conversely, a reduction of the severity of vetting can be thought of as the equivalent of delegation to an agent who is equipped with expertise and thus able to adjust policies to the state of the world. The dilemma facing new democracies transitioning from autocracy or domestic conflict is obvious to any student of principal-agent models. The agent—in this case, the staff member of the authoritarian agency—may have preferences that are so misaligned with those of the principal (the new politician) that he will use his expertise to implement policy he himself prefers. On balance, this policy outcome may be worse for the principal than his own implementation, ridden with lack of expertise as it is. Thus, in some circumstances (when preferences are completely misaligned) vetting will have a positive effect on the quality of democracy, but in others (when preferences are only somewhat misaligned) it will reduce the quality of the new democracy. The intuitions outlined earlier suggest that the mechanism behind vetting of known collaborators is very different from the mechanism behind vetting of unknown collaborators. For this reason, in our next set of regressions, we propose to disaggregate TJ vetting into: • TJ vetting of secret collaborators • TJ vetting of known collaborators We first provide a definition and illustrative example of each kind of vetting procedure. Transitional justice vetting of unknown collaborators. Unknown collaborators are those with secret ties to the former authoritarian secret police or those otherwise responsible for human rights violations. TJ vetting of unknown collaborators takes place through, for example, the opening of archives of the secret police of the former authoritarian regime to uncover who worked as a secret collaborator or informer. Proven collaborators are then either explicitly banned from holding office or a position within the state, or revealed as collaborators to the voters, who subsequently decide whether to cast their votes for the compromised politicians. A classic example of TJ vetting restricted to unknown collaborators is the Polish lustration law, which requires all persons holding or running for public office to declare in advance whether or not they had collaborated with the secret authoritarian police prior to the transition. Information from declarations admitting collaboration is put on the ballot, and voters themselves decide whether to cast their vote on a former collaborator. Negative declarations are sent to a special division of the Institute 176 Perspectives on Politics for National Remembrance, where they are verified against information assembled in the archives of the former secret political police. Proven collaborators who lied on their declarations are banned from running for office for ten years. Although this is the most cited example of TJ vetting of unknown collaborators (Kaminski and Nalepa 2006; Nalepa 2010a, 2012; Letki 2002; Williams, Fowler, and Szczerbiak2005; Szczerbiak 2002), it is hardly typical; it allows two types of collaborators to escape direct sanctions: (1) the collaborator who admits he worked as a secret collaborator29 and (2) the collaborator who failed to own up to his past but was not uncovered. A more typical vetting law carries with it an explicit sanction for anyone who is proven to have worked for the secret police as an informer (as in Hungary) or who fails to provide evidence of his or her innocence (as in the Czech Republic). Transitional justice vetting of known collaborators. This type of vetting is typically limited to the top echelon of the hierarchy of the enforcement apparatus. In other words, it discriminates between the leadership of the organization and the rank and file. A good illustration of a leadership purge is the Bulgarian Panev Law, passed by the Bulgarian National Assembly on December 9 1 992.30 Among its many provisions, the law prohibited from holding positions in "Executive Bodies of Scientific Organizations and the Higher Certifying Commission" people who had taught at the Communist Academy for Social Sciences and Social Management and those who had taught history of communist parties, Leninist or Marxist philosophy, political economy, or scientific communism. All persons covered by the law had to provide written statements regarding their prior employment and party activities. A refusal to provide such a statement was regarded as an admission of guilt. According to its author, Mr. Georgi Panev, the underlying idea behind the purge "was to bar persons of the higher totalitarian scientific structures and former collaborators of the former State Security from academic and faculty councils and from the supreme academic awards commission, awarding scientific degrees and other academic qualifications." The reason we do not consider this a purge is that instead of extending collective responsibility to anyone who taught in communist Bulgaria's academic structures, vetting was limited to those who chose to lecture at the schools training communist cadres. We can observe the usefulness of disaggregating TJ into dealing with known forms of collaboration with the ancien regime (or engagement in known human rights violations) and dealing with secret forms of collaboration (or engagement in human rights violations that have not been revealed) in figure 7 below. The left panel of the figure plots the total number of progressive transitional justice events net of regressive events as a function of time Downloaded from https://www.cambridge.org/core. IP address: 86.49.249.113, on 25 Nov 2021 at 16:17:40, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/! 0.1017/S1 537592719000756 Figure 7 Disaggregating transitional justice data Pooled g Disaggregated Transition \fear Transition \fear Table 3 Regression results using disaggregated data (Dependent variable: Power distributed by socioeconomic status) Model 7 Model 8 Model 9 Years after TJ Vetting Sev. (Pooled) TJ Vetting Sev. (Unknown) TJ Vetting Sev. (Known) Constant Random Effects: Intercept (Var.) Years after (Var.) Residual (Var.) Observations -0.010* (0.005) 0.665** (0.259) 0.453*** (0.131) 0.791 0.002 0.070 1875 -0.010** (0.005) 0.605** (0.239) 0.520*** (0.115) 0.760 0.002 0.070 1875 -0.009* (0.005) 0.179 (0.241) 0.643*** (0.109) 0.842 0.002 0.070 1875 Note: *p<0.1, **p<0.05, ***p<0.01 March 2020 | Vol. 18/No. 1 177 Downloaded from https://www.cambridge.org/core. IP address: 86.49.249.113, on 25 Nov 2021 at 16:17:40, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.Org/10.1017/S1 537592719000756 Article Accountability by Numbers Table 4 Correlation matrix of severity measures TJ vetting (unknown) TJ vetting (known) Purges Truth Commissions TJ vetting (unknown) TJ vetting (known) Purges Truth Commissions 1.00 0.16 0.22 0.14 0.16 1.00 0.48 -0.13 0.22 0.48 1.00 -0.03 0.14 -0.13 -0.03 1.00 Table 5 ANOVA tests Object Df AIC LogLik Deviance Chisq Pr(> Chisq) Baseline Model 3 (years after) 6 1021.6 -504.81 1009.6 Model 8 (TJ Vetting of unknown collaborators) 7 1018.1 -502.05 1004.1 5.5113 0.01889** Model 9 (TJ Vetting of known collaborators) 7 1023.5 -504.75 1009.5 0.1097 0.7405 Model 5 (Purges) 7 1021.2 -503.60 1007.2 2.4097 0.1206 Model 6 (Truth Commissions) 7 1023.4 504.75 1009.4 0.2271 0.6337 lapsed since the transition (upper left panel) and as a function of the year in which the transition took place (lower left panel). Here, all personnel TJ events have been pooled, and it appears evident that there is no relationship between personnel TJ and two variables that ought to be good predictors of TJ: time lapsed since transition and year of transition (Elster 2004; Huntington 1991; Barahona de Brito, Gonzalez-Enrfquez, and Aguilar 2001). However, if we disaggregate the TJ mechanisms into purges, truth commissions, TJ vetting of known collaborators, and TJ vetting of unknown collaborators, a clear pattern emerges. Consider first the lower right panel of figure 7 illustrating progressive TJ events net of regressive events for the four mechanisms as a function of transition year. TJ vetting of unknown collaborators is popular in countries that transitioned around 1990, which tend to be the Eastern European ones (Albania, Bulgaria, East Germany, Estonia, Hungary, Latvia, Poland, Slovakia, and Slovenia), as previous scholarship has speculated. Note, however, that there are also instances of TJ vetting of unknown collaborators in other countries. A deeper look into our data reveals that they are Argentina, Spain, and Guatemala. There is also an uptick in truth commissions around the beginning of the third wave of democratization, but in contrast to TJ vetting, truth commission events trend upwards again in countries with mid-1990s transitions, as well as in countries transitioning around 2010.31 This is consistent with what we know from the scholarship on truth commissions: Truth commissions abound in South America (Paraguay, Ecuador, Peru) and Africa (Kenya, South Africa 178 Perspectives on Politics and Liberia); they can also be found in Indonesia and East Germany (United States Institute of Peace 2011a, 2011b, 2011c, 201 Id, 201 le, 201 If, 201 lh, 2011i; Gibson 2006). The story with purges and TJ vetting of known collaborators is quite different. First, the occurrence of purges is flat across the range of transition years in our dataset. If they do occur, they occur in the immediate aftermath of the democratic transition (as indicated by the slight uptick on the left end of the upper right panel of figure 7). TJ vetting of known collaborators, on the other hand, seemed to have been more popular at the beginning of the Third Wave transitions (in Latin American countries that transitioned in the 1970s and 1980s), and their popularity seems to have increased again after 2005. As in the case of purges, they are concentrated in the early post-transition years. The upper panel of figure 7 shows that the timing of TJ vetting of unknown collaborators clearly differs from the timing of purges and of TJ vetting of known collaborators. Whereas the latter take place in the immediate aftermath of transitions to democracy, TJ vetting of unknown collaborators peaks about ten years following the transition. Truth commissions are implemented soon after the transition or conflict termination but continue to be implemented longer than purges or TJ vetting of unknown collaborators. In sum, patterns of purge activity and TJ vetting of known collaborators are not the same as patterns of TJ vetting of unknown collaborators and truth commission activity. Similar inferences can be drawn from the GIS-coded version of our data in the form of world maps illustrating all three of our measures. Geocoded values of Downloaded from https://www.cambridge.org/core. IP address: 86.49.249.113, on 25 Nov 2021 at 16:17:40, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/! 0.1017/S1 537592719000756 severity, volatility, and urgency for TJ vetting of unknown collaborators, truth commissions, purges, and TJ vetting of known collaborators are provided in online appendix B.32 The regression table corroborates this intuition. For comparison's sake, we have included model 4 from table 2, that is, the regression with the pooled category of TJ vetting, as model 7. Models 8 and 9 have this independent variable separated into two categories: TJ vetting of known and unknown collaborators and perpetrators of human rights violations. The results in model 8 in particular suggest that the TJ vetting of unknown collaborators is the driver behind TJ vetting having a significant effect on the relationship between wealth and the distribution of political power.33 That coefficient remains significant (though slightly smaller), while the coefficient on TJ vetting of known collaborators (model 9) completely loses significance. This supports our initial theory about the differential effects of vetting that reveals new information about the nature of collaboration with the former authoritarian regime or behavior under conflict. Furthermore, it is clear that the differential effect in our regression is not the result of time lapsed since the transition for two reasons. First, we measure severity at the country level as a proportion of progressive TJ vetting events over all events, progressive and regressive. Second, and more importantly, this effect holds even after accounting for years lapsed since the transition. In this set of regressions, just as in the previous ones, presented in table 2, we decided to forgo including all the transitional justice mechanisms in one regression, because some of them are highly correlated with one another, as table 4 indicates. Instead of saturating the regression model, we can compare all the models against one another using an ANOVA test. In this test, we compare the baseline model (model 3 from table 3), which uses only years since the transition as a predictor, against each of the models that additionally incorporate the severity of each transitional justice mechanism. The results indicate that only the model including the severity of TJ vetting of unknown collaborators is significantly different (with a p-value of .019) from the baseline model in its predictive power. Table 5 also presents the log-likelihood of all models as well as the Akaike Information Criterion. As a general rule of thumb, the smaller these values are, the better the fit of the model. The values of the measures corresponding to the TJ vetting of unknown collaborators model are clearly smaller than those of the others. Conclusion We have introduced a new dataset on transitional justice, that is, on how new democracies recovering from authoritarianism or civil war deal with members of and collaborators with former authoritarian regimes. Our dataset is innovative in a number of ways. First, it records personnel transitional justice as events unfolding over time following the year of transition. This allows us to account for instances of delayed TJ as well as of TJ reversals. It also allows us to design innovative ways of measuring TJ severity and volatility. We encourage scholars to use our personnel TJ events data as building blocks for constructing new measures motivated by their specific theoretical interests. A second innovation of our dataset is that it parses out similar yet distinct ways of dealing with personnel of the former authoritarian regime. First, it separates purges from TJ vetting. In a second step, it distinguishes between two forms of TJ vetting: (1) the removal from office of elites whose actions under the former authoritarian regime were known or perpetrators who committed crimes that are common knowledge, and (2) vetting that relies on revealing information that was kept secret. We also summarize an argument according to which the TJ vetting of unknown collaborators ought to be more conducive to democratic stability than purges. This argument follows from an assumption that revealing secret information prevents blackmail by those with access to skeletons in the closets of former collaborators and perpetrators who now hold positions of power (Ang and Nalepa 2019). In contrast, the only outcome achieved by purges and the vetting of known collaborators is the removal from office of elites whose expertise could be useful to new democracies. To test this hypothesis about the differential effects of TJ vetting we regress a V-Dem variable that operationalizes the turnover of authoritarian elites34 on the severity of truth commissions, purges, and TJ vetting. First, we find support for the theory that the severity of TJ vetting indeed improves the turnover of authoritarian elites, but no such support for the other forms of personnel transitional justice. Second, upon disaggregating TJ vetting into mechanisms dealing with known and unknown collaborators, we only find this effect in TJ dealing with unknown collaborators. Future research could operationalize the power of authoritarian elites more directly by, for instance, tracing the extent to which authoritarian elites reproduce themselves under the new democratic conditions. Future research could also extend the data collection back to 1918 to incorporate countries from the second wave of democratization, especially those in Western Europe. A third innovation could include applying our technique to events associated with trials, thus creating a time series of progressive and regressive trial events. Given the extensive literature on the effects of criminal trials as part of transitional justice, it would be fascinating to compare the effects of trials to the effects of TJ vetting of elites. March 2020 | Vol. 18/No. 1 179 Downloaded from https://www.cambridge.org/core. IP address: 86.49.249.113, on 25 Nov 2021 at 16:17:40, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.Org/10.1017/S1 537592719000756 Article Accountability by Numbers Notes 1 See, for instance, Mallinder 2008, Olsen, Payne, and Reiter 2010b, and most notably Sikkink and Walling 2007, Dancy and Wiebelhaus-Brahm 2017, and the ongoing efforts of the Transitional Justice Research Collaborative (TJRC), Dancy and Montal 2017, and Dancy and Michel 2016. 2 For other excellent arguments of why limiting the focus of TJ to trials is misleading see Murphy 2017. 3 As an example of a failed apology, consider Alexander Kwasniewski's recognition of Jews murdered in Jedwabne, a Polish town under the occupation of Nazi Germany. Kwasniewski apologized on behalf of the Polish people, but the apology failed at reconciling Jews and Poles because Kwasniewski stressed that the truth of what happened in Jedwabne was yet been established (Keesing's Record of World Events 2001). As an example of a successful apology, consider the one by Roman Herzog, issued while attending the fiftieth anniversary of the Warsaw Uprising in 1994, for the suffering Germany caused Poland during World War II. 4 Indeed, most contributions to the lustration literature suggest that this kind of TJ policy is limited to post-communist Europe; De Greiffand Mayer-Rieckh 2007; Ellis 1996; Closa Montero 2010; Letki 2002; Stan 2013; Stan and Nedelsky 2015. 5 We note that Olsen, Payne, and Reiter 2010a only include truth commissions in regressions as explanatory variables, but even these are marginally significant for only one type of outcome variables—variously constructed terror scales. 6 David defines lustration as a "special public employment law that stipulates the conditions for the access of persons who worked for or collaborated with the political or repressive apparatus of socialist regimes to certain public positions in new democracies." 7 The TJDB includes data on five transitional justice mechanisms including amnesties, trials, truth commissions, lustrations, and reparations. The Transitional Justice Research Collaborative covers amnesties, trials (including domestic, foreign, international and civil), vetting, truth commissions, reparations, and customary justice 8 In line with Home 2017b we will use the term TJ vetting as synonymous with lustration. 9 Childs and Popplewell 2016 report that most of the Stasi employees had to turn to some other means of earning their living. However a significant number did find reemployment in private security. In Saxony, it was reported that more than 500 ex-Stasi operatives had been taken over by the police. This includes 161 former full time Ministry for State Security employees and 262 unofficial collaborators. In addition, 370 ex-members of the DDR criminal police were in employment in 1994 (195). 180 Perspectives on Politics 10 Since our dataset extends to post-conflict situations, we broaden the set of offenses subject to vetting to include perpetrators of human rights violations. 11 The full name was "Law On Genocide and Crimes against Humanity Committed in Albania during Communist Rule for Political, Ideological or Religious Motives." 12 Specifically, it was established via the Promotion of National Union and Reconciliation Act, passed by the South African parliament in July 1995; United States Institute of Peace 201 lj. 13 As testimony to the non-criminal character of the commission's work, consider its chairman's insistence that "the major task of his commission was not to bring the wrongdoers to justice but to find out the truth of the events during the April-May 2010 protests so the public would be informed in order to ensure that incidents of this kind were not repeated"; Rustici and Sander 2012. 14 Examples of such countries include Russia, Egypt, and Thailand. 15 Examples of each includes Cyprus, which is excluded from GWF based on size, and Kenya, which is excluded despite its Post-Election Violence in 2007-2008. Although the Post-Election Violence in Kenya was excluded from PCJ, it produced numerous domestic transitional justice events, including the creation of a truth commission. 16 A list of these secondary sources is available here: https://tinyurl.com/ybmcj7hf. 17 Note that this categorization of events is not intended to reflect the normative implications of a given event. The striking down of a TJ law that violates individual protections, for example, may be a normatively positive event, but it nevertheless weakens the TJ process. Thus, all such events are categorized as "regressive" events. 18 We mention, for instance, that among the events included in our chronologies are ones that could not be classified as purges, vetting, or truth commissions. These were labeled "non-events" and include trials, amnesties, and victim compensation. Other researchers may want to create their own categories out of these events, a project made possible by our organization of the chronologies. Moreover, our technique of labeling events as progressive or regressive could be fruitfully applied to criminal trials. The initiation of an investigation, along with an indictment, could be the first progressive event in a trial proceeding. Reducing the number of counts on which a defendant would be charged would be a regressive event, as would acquittal or the commuting of a sentence. 19 Nigeria's time series is censored at 2016, because our data collection ends with 2016. In other words, we are not Downloaded from https://www.cambridge.org/core. IP address: 86.49.249.113, on 25 Nov 2021 at 16:17:40, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/! 0.1017/S1 537592719000756 capturing the events that will happen at a future time. Censorship is a problem for all countries that do not end with an authoritarian reversal by 2016, but is most acute in the case of states that transitioned more recendy. 20 We clarify that in all three measures subscripts do not represent exponents, but time indices. 21 T^ need not be the same as 2016, as illustrated by the case of Thailand, which experienced a military coup in 2014. 22 In countries like Thailand, 71 will be subtracted from the year of the authoritarian reversal rather than from 2016. 23 We code the data beginning with the first year after the transition, which is consistent with the fact that the first progressive event has to take place after the transition. 24 Any measure seeking to show the variation between these two extreme cases should note the direction of the timing of TJ. Therefore, we use the language of "urgency" and "delay" to explain this measure rather than simply "timing" because the value of the measure increases when the TJ process is implemented shortly after the transition. 25 Answers to the question were distributed along a 5-point scale. The possible answers included: (0) "Wealthy people enjoy a virtual monopoly on political power. Average and poorer people have almost no influence"; (1) "Wealthy people enjoy a dominant hold on political power. People of average income have little say. Poorer people have essentially no influence"; (2) "Wealthy people have a very strong hold on political power. People of average or poorer income have some degree of influence but only on issues that matter less for wealthy people"; (3) "Wealthy people have more political power than others. But people of average income have almost as much influence and poor people also have a significant degree of political power"; and (4) "Wealthy people have no more political power than those whose economic status is average or poor. Political power is more or less equally distributed across economic groups" (Coppedge et al. 2017b). 26 PdSES is also a particularly reasonable measure of quality of democracy for our purposes because while it measures an important aspect of democracy, it is unlikely to be correlated with rule of law, which could also affect the implementation of transitional justice. 27 The reason our number of cases drops from 84 to 83 is that Grenada is not coded in V-Dem. 28 Since severity of all mechanisms is measured on the same 0-1 scale, such comparisons of magnitude of the coefficients are warranted. 29 See Nalepa 2008 for a discussion of whether a positive declaration is, indeed, not a sanction. 30 The full name of the bill was "Law for Temporary introduction of Additional Requirements for Members of Executive Bodies of the Scientific Organizations and the Higher Certifying Commission." 31 These include the Arab Spring countries—Tunisia and Egypt—as well as several countries in South and Southeast Asia. 32 They are also available at an interactive website: https://tinyurl.com/ybmcj7hf. 33 Recall that higher values of PdSES mean lower correlation of wealth with political power. 34 Recall that this is measured by the extent to which economic wealth translates into political power; Coppedge et al. 2017b. Supplementary Materials A. Statistical Appendix B. GIS Appendix To view supplementary material for this article, please visit https://d0i.0rg/l0.1017/S1537592719000756 References Albertus, Michael and Victor Menaldo. 2014. "Gaming Democracy: Elite Dominance during Transition and the Prospects for Redistribution." British Journal of Political Science 44(3): 575-603. Alivizatos, Nicos C. and P. Nikiforos Diamandouros. 1997. Politics and the Judiciary in the Greek Transition to Democracy. Notre Dame, IN: University of Notre Dame Press. Anaba, Innocent. 2001. "Nigeria: Appeal Court Asked To Determine Legality Of Oputa Panel." The Vanguard Daily, February 28 (https://allafrica.com/stories/ 200102280103.html), accessed October 18, 2018. Bakiner, Onur. 2016. Truth Commissions: Memory, Power, and Legitimacy. Philadelphia: University of Pennsylvania Press. Barahona de Brito, Alexandra, Carmen Gonzalez-Enrfquez, and Paloma Aguilar, eds. 2001. The Politics of Memory: Transitional Justice in Democratizing Societies. Oxford: Oxford University Press. Bermeo, Nancy. 2016. "On Democratic Backsliding." Journal of Democracy 27'(1): 5-19. Binningsbo, Helga Malmin, Cyanne E Loyle, Scott Gates, and Jon Elster. 2012. "Armed Conflict and Post-Conflict Justice, 1946-2006: A Dataset." Journal of Peace Research 49(5): 731-40. Borchert, Jürgen. 2006. Die Zusammenarbeit des Ministeriums fur Staatssicherheit (MfS) mit dem sowjetischen KGB in den 70er und 80er Jahren: ein Kapitel aus der Geschichte der SED-Herrschaft. Münster: LIT Verlag. Brun, Diego Abente and Larry Diamond. 2014. Clientel-ism, Social Policy, and the Quality of Democracy. Baltimore, MD: Johns Hopkins University Press. March 2020 | Vol. 18/No. 1 181 Downloaded from https://www.cambridge.org/core. IP address: 86.49.249.113, on 25 Nov 2021 at 16:17:40, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.Org/10.1017/S1 537592719000756 Article Accountability by Numbers Childs, David and Richard Popplewell. 2016. The Stasi: The East German Intelligence and Security Service. London: Palgrave Macmillan. Cinar, Ipek. 2017. "Democracy Dismanded: Strategic Choices of the Would-be Autocrats." Working Paper, University of Chicago. Closa Montero, Carlos. 2010. "Study on How the Memory of Crimes Committed by Totalitarian Regimes in Europe Is Dealt with in the Member States." Madrid: Institute for Public Goods and Policy. Congreso de los Diputados, Comisiön de Cultura. 2013. "161/002111." Boletin Oficial de Las Cortes Generales D(360): 27-28. Coppedge, Michael. 2012. Democratization and Research Methods. Cambridge, UK: Cambridge University Press. Coppedge, Michael, John Gerring, Staffan I. Lindberg, Svend-Erik Skaaning, Jan Teorell, David Altman, Michael Bernhard, M. Steven Fish, Adam Glynn, Allen Hicken, Carl Henrik Knutsen, Joshua Krusell, Anna Luhrmann, Kyle L. Marquardt, Kelly McMann, Valeriya Mechkova, Moa Olin, Pamela Paxton, Daniel Pemstein, Josefine Pernes, Constanza Sanhueza Petrarca, Johannes von Romer, Laura Saxer, Brigitte Seim, Rachel Sigman, Jeffrey Staton, Natalia Stepanova, and Steven Wilson. 2017a. "V-Dem Country-Year/ Country-Date Dataset v7.1." University of Gothenburg: Varieties of Democracy Institute. Coppedge, Michael, John Gerring, Staffan I. Lindberg, Svend-Erik Skaaning, Jan Teorell, Michael Bernhard, David Altman, M. Steven Fish, Adam Glynn, Allen Hicken, Carl Henrik Knutsen, Kyle L. Marquardt, Valeriya Mechkova Kelly McMann, Pamela Paxton, Daniel Pemstein, Laura Saxer, Brigitte Seim, Rachel Sigman, and Jeffrey Staton. 2017b. "V-Dem Codebook v7.1.". University of Gothenburg: Varieties of Democracy Institute. Dancy, Geoff and Veronica Michel. 2016. "Human Rights Enforcement from Below: Private Actors and Prosecutorial Momentum in Latin America and Europe." International Studies Quarterly 60(1): 173-88. Dancy, Geoff and Florencia Montal. 2017. "Unintended Positive Complementarity: Why International Criminal Court Investigations May Increase Domestic Human Rights Prosecutions." American Journal of International Law 111(3): 689-723. Dancy, Geoff and Eric Wiebelhaus-Brahm. 2018. "The Impact of Criminal Prosecutions during Intrastate Conflict." Journal of Peace Research 55(1): 47-61. David, Roman. 2011. Lustration and Transitional Justice: Personnel Systems in the Czech Republic, Hungary, and Poland. Philadelphia: University of Pennsylvania Press. De Greiff, Pablo and Alexander Mayer-Rieckh. 2007. Justice as Prevention: Vetting Public Employees in Transitional Societies. New York: Social Science Research Council. 182 Perspectives on Politics Ellis, Mark S. 1996. "Purging the Past: The Current State of Lustration Laws in the Former Communist Bloc." Law and Contemporary Problems 59(4): 181-96. Elster, Jon. 2004. Closing the Books: Transitional Justice in Historical Perspective. Cambridge, UK: Cambridge University Press. Escribä-Folch, Abel and Joseph Wright. 2015. "Human Rights Prosecutions and Autocratic Survival." International Organization 69(2): 343-73. Finch, W. Holmes, Jocelyn E. Bolin, and Ken Kelley. 2014. Multilevel modeling using R. New York: Routledge. Geddes, Barbara, Joseph Wright, and Erica Frantz. 2014. "Autocratic Breakdown and Regime Transitions: A New Data Set." Perspectives on Politics 12(2): 313-31. Gibson, James L. 2006. "Overcoming Apartheid: Can Truth Reconcile a Divided Nation?" Annals of the American Academy of Political and Social Science 603(1): 82-110. Goertz, Gary. 2006. Social Science Concepts: A User's Guide. Princeton, NJ: Princeton University Press. Grzymala-Busse, Anna M. 2002. Redeeming the Communist Past: The Regeneration of Communist Parties in East Central Europe. New York: Cambridge University Press. Haggard, Stephen and Robert Kaufmann. 2016. Dictators and Democrats: Masses, Elites, and Regime Change. Princeton, NJ: Princeton University Press. Hatschikjan, Magarditsch, Dušan Reljič, and Nenad Šebek eds. 2005. "Disclosing Hidden History: Lustration in the Western Balkans." Thessaloniki: Center for Democracy and Reconciliation in Southeast Europe. Belgrade: Cicero. Hayner, PriscillaB. 1994. "Fifteen Truth Commissions— 1974 to 1994: A Comparative Study." Human Rights Quarterly 16(4): 597-655. -. 2001. Unspeakable Truths: Confonting State Terror and Atrocity. Hove, UK: Psychology Press. -. 2011. Unspeakable Truths: Transitional Justice and the Challenges of Truth Commissions. New York: Routledge. Home, Cynthia. 2017a. "Vetting, Purges, and Lustration: Measurement Choices and Empirical Implications." Conference Proceedings of the American Political Science Association Meeting, September 2. -. 2017b. Building Trust and Democracy in Transition: Assessing the Impact of Transitional Justice in Post-Communist Countries. Oxford: Oxford University Press. Human Rights Watch. 1991. "Human Rights in Post-Invasion Panama: Justice Delayed Is Justice Denied." B304. New York: Human Rights Watch. -. 2008. "Ballots to Bullets: Organized Political Violence and Kenya's Crisis of Governance." 20(1A). New York: Human Rights Watch. Huntington, Samuel P. 1991. The Third Wave: Democratization in the Late Twentieth Century. Norman: University of Oklahoma Press. Downloaded from https://www.cambridge.org/core. IP address: 86.49.249.113, on 25 Nov 2021 at 16:17:40, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/! 0.1017/S1 537592719000756 International Center for Transitional Justice. 2011. "The Kenyan Commission of Inquiry into Post-Election Violence." -. 2014. "Kenya TJRC Final Report Deserves Serious Analysis and Action." Jenne, Erin K. and Cas Mudde. 2012. "Can Outsiders Help?" Journal of Democracy 23(3): 147-55. Kaminski, Marek M. and Monika Nalepa. 2006. "Judging Transitional Justice: A New Criterion for Evaluating Truth Revelation Procedures." Journal of Conflict Resolution 50(3): 383-408. Kaminski, Marek M., Monika Nalepa, and Barry O'Neill. 2006. "Normative and Strategic Aspects of Transitional Justice." Journal of Conflict Resolution 50(3): 383-408. Keesing's Record of World Events. 1974. "Announcement of General Election Date. - Resumption of Party Politics. — Other Internal Developments." 20: 26781. -. 1998. "South Africa." 44: 42536. -. 2001. "Life Expectancy." 47(7): 44275. Kitschelt, Herbert, Zdenka Mansfeldova, Radoslaw Markowski, and Gabor Toka. 1999. Post-Communist Party Systems: Competition, Representation, and Inter-Party Cooperation. New York: Cambridge University Press. Koehler, John O. 1999. STASI: The Untold Story of the East German Secret Police. New York: Basic Books. Krauss, Clifford. 2000. "New Argentine President Orders Purge of'Dirty War' Remnants." New York Times, February 16, 6. Kreutz, Joakim. 2010. "How and When Armed Conflicts End: Introducing the UCDP Conflict Termination Dataset." Journal of Peace Research 47(2): 243-50. Letki, Natalia. 2002. "Lustration and Democratisation in East-Central Europe." Europe-Asia Studies 54(4): 529- 52. Lust, Ellen and David Waldner. 2015. "Unwelcome Change: Understanding, Evaluating, and Extending Theories of Democratic Backsliding." US Agency for International Development (https://pdf.usaid.gov/ pdf_docs/PBAAD635.pdf), accessed October 15, 2018. Mallinder, Louise. 2008. Amnesty, Human Rights and Political Transitions: Bridging the Peace and Justice Divide. Oxford: Bloomsbury Publishing. Miller, John. 1998. "Settling Accounts with a Secret Police: The German Law on the Stasi Records." Europe-Asia Studies 50(2): 305-30. Mopheme/The Survivor (Maseru). 2000a. "Lesotho: 1998 Revisited—Do You Know Anything?" Mophemel The Survivor (Maseru), April 5 (https://allafrica.com/ stories/200004050126.html), accessed October 15, 2018. -. 2000b. "Lesotho: 'Sephetho Commission' Delayed by Court Action." Mopheme/The Survivor (Maseru) April 26 (https://allafrica.com/stories/ 200004260168.html), accessed October 15, 2018. -. 2002. "Lesotho: Senate Motion Calls for Unity." Mopheme/The Survivor (Maseru). Murphy, Colleen. 2017. The Conceptual Foundations of Transitional Justice. New York: Cambridge University Press. Nalepa, Monika. 2008. "To Punish the Guilty and Protect the Innocent Comparing Truth Revelation Procedures." Journal ofTheoretical Politics 20(2): 221— 45. -. 2010a. "Captured Commitments: An Analytic Narrative of Transitions with Transitional Justice." World Politics 62(2): 341-80. -. 2010b. Skeletonsin the Closet: Transitional Justice in Post-Communist Europe. New York: Cambridge University Press. -. 2012. "Tolerating Mistakes: How Do Popular Perceptions of Procedural Fairness Affect Demand for Transitional Justice?" Journal of Conflict Resolution 56(3): 490-515. -. 2013. "Lustration as a Trust-Building Mechanism? Transitional Justice in Poland." In After Oppression, eds. Vasily Popovski and Monica Serrano, 333-362. New York: United Nations Press. Olsen, Tricia D., Leigh A. Payne, and Andrew G Reiter. 2010a. "The Justice Balance: When Transitional Justice Improves Human Rights and Democracy." Human Rights Quarterly 32(4): 980-1007. -. 2010b. "Transitional Justice in the World, 1970— 2007: Insights from a New Dataset." Journal of Peace Research 47(6): 803-09. Pambazuka News. 2005. "Nigeria: Human Rights Report Released." Pambazuka News. January 27 (https://alla-frica.com/stories/200501270670.html), accessed October 15, 2018. Pinto, Antonio Costa. 2001. "Settling Accounts with the Past in a Troubled Transition to Democracy: The Portuguese Case." The Politics of Memory: Transitional Justice in Democratizing Societies, Alexandra Barahona De Brito, Carmen Gonzalez Enriquez, Paloma Aguilar, 65-91. Oxford: Oxford University Press. Posner, Eric A. and Adrian Vermeule. 2004. "Transitional Justice as Ordinary Justice." Harvard law Review 117(3): 761-825. Raudenbush, Stephen W. and Anthony S. Bryk. 2002. Hierarchical linear Models: Applications and Data Analysis Methods. Vol. 1. Newbury Park, CA: Sage. Rustici, Kathleen and Alexandra Sander. 2012. "Thailand's Truth for Reconciliation Commission Issues Final Report." Washington, DC: Center for Strategic International Studies. Schwartz, Herman. 2000. The Struggle for Constitutional Justice in Post-Communist Europe. Chicago: University of Chicago Press. March 2020 | Vol. 18/No. 1 183 Downloaded from https://www.cambridge.org/core. IP address: 86.49.249.113, on 25 Nov 2021 at 16:17:40, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.Org/10.1017/S1 537592719000756 Article Accountability by Numbers Sedelmeier, Ulrich. 2014. "Anchoring Democracy from Above? The European Union and Democratic Backsliding in Hungary and Romania after Accession." JCMS: Journal of Common Market Studies 52(1): 105-21. Serra, Gilles. 2012. "The Risk of Partyarchy and Democratic Backsliding Mexico's 2007 Electoral Reform." Taiwan Journal of Democracy 8(1): 93-118. Siegel, Richard L. 1998. "Transitional Justice: A Decade of Debate and Experience." Human Rights Quarterly 20(2): 431-54. Sikkink, Kathryn and Carrie Booth Walling. 2007. "The Impact of Human Rights Trials in Latin America." Journal of Peace Research 44(4): 427-45. Stan, Lavinia. 2013. "Reckoning with the Communist Past in Romania: A Scorecard." Europe-Asia Studies 65(1): 127-46. Stan, Lavinia and Nadya Nedelsky. 2015. Post-Communist Transitional Justice: Lessons fiom Twenty-five Years of Experience. New York: Cambridge University Press. Stan, Lavinia. et al. 2009. Transitional Justice in Eastern Europe and the Former Soviet Union: Reckoning with the Communist Past. New York: Routledge. Svolik, Milan W. 2017. "When Polarization Trumps Civic Virtue: Partisan Conflict and the Subversion of Democracy by Incumbents." Unpublished Manuscript, Yale University. Szczerbiak, Aleks. 2002. "Dealing with the Communist Past or the Politics of the Present? Lustration in Post-communist Poland." Europe-Asia Studies 54(4): 553-72. Teitel, Ruti G. 2000. Transitional Justice. New York: Oxford University Press. Thorns, Oskar N. T, James Ron, and Roland Paris. 2010. "State-level Effects of Transitional Justice: What Do We Know?" International Journal of Transitional Justice 4(3): 329-54. Tillack, Hans-Martin. 2007. "A Tale of Gazoviki, Money and Greed." Stern Magazine, 192. Todd, Stephen Charles, et al. 2000. Lysias. Vol. 2. Austin: University of Texas Press. Truth for Reconciliation Commission of Thailand. 2012. "Final Report of Truth for Reconciliation Commission of Thailand (TRCT) July 2010-July 2012. Bangkok. Ughegbe, Lemmy. 2003. "Nigeria: Oputa Panel Has No Powers—Supreme Court." Vanguard Daily, February 1. UN Integrated Regional Information Networks (Nairobi). 2011. "Comoros; Missing Guns Delay Demobilization Process." Africa News. United States Institute of Peace. 2011a. "Truth Commission: Ecuador 96." United States Institute of Peace Truth Commission Digital Archive (https://www. usip.org/ publications/1996/09/truth-commission-ecuador-96), accessed October 18, 2018. 184 Perspectives on Politics -. 2011b. "Truth Commission: Ecuador 07." United States Institute of Peace Truth Commission Digital Archive (https://www.usip.org/publications/2007/05/ truth-commission-ecuador-07), accessed October 18, 2018. -. 201 lc. "Truth Commission: Germany 92." United States Institute of Peace Truth Commission Digital Archive, (https://www.usip.org/publications/1992/05/ truth-commission-germany-92), accessed October 18, 2018. -. 201 Id. "Truth Commission: Germany 95." United States Institute of Peace Truth Commission Digital Archive (https://www.usip.org/publications/1995/07/ truth-commission-germany-95), accessed October 18, 2018. -. 20 lie. "Truth Commission: Kenya." United States Institute of Peace Truth Commission Digital Archive (https://www.usip.org/publications/2009/07/truth-commission-kenya), accessed October 18, 2018. -. 201 If. "Truth Commission: Liberia." United States Institute of Peace Truth Commission Digital Archive. (https://www.usip.org/publications/2006/02/truth-commission-liberia), accessed October 18, 2018. -. 201 lg. "Truth Commission: Nigeria." United States Institute of Peace Truth Commission Digital Archive, (https://www.usip.org/publications/1999/ 06/truth-commission-nigeria), accessed October 18, 2018. -. 201 lh. "Truth Commission: Paraguay." United States Institute of Peace Truth Commission Digital Archive, (https://www.usip.org/publications/2004/06/ truth-commission-paraguay), accessed October 18, 2018. -. 201 li. "Truth Commission: Peru 01." United States Institute of Peace Truth Commission Digital Archive, (https://www.usip.org/publications/2001/07/ truth-commission-peru-01), accessed October 18, 2018. -. 201 lj. "Truth Commission: South Africa." United States Institute of Peace Truth Commission Digital Archive, (https://www.usip.org/publications/1995/12/ truth-commission-south-africa), accessed October 18, 2018. Van der Merwe, Hugo, Victoria Baxter, and Audrey R. Chapman. 2009. Assessing the Impact of Transitional Justice: Challenges for Empirical Research. Washington, DC: US Institute of Peace Press. Vinjamuri, Leslie and Jack Snyder. 2004. "Advocacy and Scholarship in the Study of International War Crime Tribunals and Transitional Justice." Annual Review of Political Science 7: 345-62. Williams, Kieran, Brigid Fowler, and Aleks Szczerbiak. 2005. "Explaining Lustration in Central Europe: A Post-Communist Politics Approach." Democratization 12(1): 22-43. Downloaded from https://www.cambridge.org/core. IP address: 86.49.249.113, on 25 Nov 2021 at 16:17:40, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.Org/10.1017/S1 537592719000756