Spoilers of peace: Pro-government militias as risk factors for conflict recurrence

This article introduces the global Pro-Government Militias Database (PGMD). Despite the devastating record of some pro-government groups, there has been little research on why these forces form, under what conditions they are most likely to act, and how they affect the risk of internal conflict, repression, and state fragility. From events in the former Yugoslavia, Iraq, Sudan, or Syria and the countries of the Arab Spring we know that pro-government militias operate in a variety of contexts. They are often linked with extreme violence and disregard for the laws of war. Yet research, notably quantitative research, lags behind events. In this article we give an overview of the PGMD, a new global dataset that identifies pro-government militias from 1981 to 2007. The information on pro-government militias (PGMs) is presented in a relational data structure, which allows researchers to browse and download different versions of the dataset and access over 3,500 sources that informed the coding. The database shows the wide proliferation and diffusion of these groups. We identify 332 PGMs and specify how they are linked to government, for example via the governing political party, individual leaders, or the military. The dataset captures the type of affiliation of the groups to the government by distinguishing between informal and semi-official militias. It identifies, among others, membership characteristics and the types of groups they target. These data are likely to be relevant to research on state strength and state failure, the dynamics of conflict, including security sector reform, demobilization and reintegration, as well as work on human rights and the interactions between different state and non-state actors. To illustrate uses of the data, we include the PGM data in a standard model of armed conflict and find that such groups increase the risk of civil war.

Post-civil conflict demobilisation research usually focuses on rebel disarmament and overlooks the non-state militias that helped incumbent regimes retain power. Despite being allied to the government, pro-government militias can pose a long-term threat to the state if not eliminated or integrated. We argue that post-war militia management politics are driven by structural factors and elite concerns for regime survival. Quantitative analyses show that post-war pro-government militias survive longer in autocracies compared to when democratic regimes have defeated a rebellion. The findings paint a more complete picture of armed group demobilisation and have implications for post-war repression, democratisation and conflict recurrence.

The Taliban’s victory in Afghanistan in 2021 has led to calls for a review of counterinsurgency strategy. One aspect of COIN strategy in Afghanistan was the use of militias in the anti-insurgent campaign the Taliban. As well as their use in Afghanistan, states have successfully countered insurgent violence through the deployment of, or cooperating with, pro-government militias elsewhere. Indeed, between 1981 and 2014, more than 504 militias were active across the world, 1 1 Sabine Carey, et al., ‘The Life, Death and Diversity of Pro-Government Militias: The Fully Revised Pro-Government Militias Database Version 2.0’, Research and Politics 9/1 (2022). of which many were identified as anti-insurgent non-state forces in counter-rebel campaigns. Taking Colombia and Philippines as two contemporary cases, this paper will explore the limited contributions of anti-insurgent militias (such as the Autodefensas Unidas de Colombia and the Manila Crusaders for Peace and Democracy) in counterinsurgency campaigns. The paper will seek to identify the reasons why these armed groups produce contributions in countering armed rebels. These case studies are diverse and both have faced highly adaptable and unique rebel campaigns. Both highlight how the use of militias as counterinsurgency mechanisms can yield positive results. Using evidence from both case studies (government reports, primary archives etc.), I provide evidence of how militias can produce valuable results for a government’s anti-insurgent campaign.

Previous research on non-state actors involved in civil wars has tended to disregard the role of extra-dyad agents in influencing conflict outcomes. Little is known as to whether the presence of such extra-dyadic actors as pro-regime militias affects conflict termination and outcomes. This article develops and tests a number of hypotheses on the pro-government militias’ effect upon civil war outcomes. It proposes that pro-regime militias involved in intrastate conflicts tend to act as proponents of ‘no peace, no war’, favouring low-activity violence and ceasefires over other conflict outcomes. These hypotheses are examined using an expanded dataset on pro-government militias and armed conflict in a statistical analysis of 229 civil war episodes from 1991 to 2015. These findings shed new light on the role of extra-state actors in civil wars.

Although the existing literature on Pro-Government Militias (PGMs) is rife with studies on various aspects of government-militia relations, not much is known about specific approaches that governments employ to ensure loyalty of their semi-formal proxies. Lessons from recent civil war in Sudan and other cases of PGMs turning their arms against their former patrons further enhance the importance of understanding which mechanisms (if any) incumbents deploy to prevent militias from “going rogue.” In this study, we examine three mechanisms employed by governments to guarantee loyalty of their militia allies. We emphasize the importance of personal, sectarian and other ideological fractionalization within rebel groups; deployment of extreme violence by PGMs against co-ethnic civilians; and formation of rival militias as the most effective PGM loyalty assurance tools available to the incumbents. We test these theoretical assumptions on the case study of the Second Chechen War to elucidate how each of these mechanisms was implemented in practice during the decades-long counterinsurgency campaign waged by Moscow.

Purpose: To comparing the survival in different strategies, preoperative systemic treatment (PST) versus upfront surgery (US) in patients of HER2-positive early breast cancer in real-world.Methods: Eligible patients from 2012 to 2015 were classified as PST or US group prospectively, according to the real upfront treatment. The primary endpoint is disease-free survival (DFS), the second endpoint is overall survival (OS). All the outcomes were examined in unadjusted model, propensity score matching (PSM) model, and inverse probability of treatment weighting (IPTW) model. Results: Finally, 1067 eligible patients (215 in PST group, 852 in US group) were included into analysis (Table 1). In unweighted analysis, the cumulative DFS of PST group was significantly lower than US group (78.1% vs 87.7%, P<0.001), especially for those did not reach pathological complete response after PST. After adjusting the parameters, in PSM model (matching at 1:1 ratio), the DFS of PST group was significantly higher than the DFS of US group (HR, 0.57s2, 95%CI, 0.371~0.881, P, 0.012). In IPTW model, there was no significant difference of DFS between two groups (HR, 0.946, 95%CI, 0.763~1.172, P, 0.609). For OS, there were no significant difference between two groups in all three models. Conclusions: The patients in PST group have worse DFS than those in US group, mainly because of the unbalancing stage and biological risk. By real-world statistic method, after adjusting and making parameters comparable, the DFS of PST group is non-inferiority to the DFS of US group in IPTW model and even superior to US group in PSM model. *Proportions and medians are weighted using IPTW, all covariates included in the propensity analysis. Abbreviations: PSM, propensity score matching, IPTW, inverse probability of treatment weighting, PST, preoperative systemic treatment, US, upfront surgery, SMD, standardized mean difference, ER, estrogen receptor, PR, progesterone receptor.In IPTW model, the DFS rate of the PST group was 81.3% versus 80.8% of the US group, and the OS rate of the PST group was 92.1% versus 90.3% (Figure 2E, 2F), both having no significantly differences (Table 4). In further stratified analysis (Figure 3E, 3F), as in PSM model, the DFS and OS rate of the patients without pCR after PST (73.1%, 88.4%) were worse than those with pCR (96.6%, 99.3%) and US group (80.8%, 90.3%), respectively. Table 1. The clinicopathologic characteristics of two groups in PSM and IPTW modelsCharacteristicsNumber of casesUnweighted primary samplePSM modelIPTW model*PST group (215)US group (852)SMDPST group (145)US group (145)SMDPST group (765)US group (1021)SMDN (%)N (%)N (%)N (%)N (%)N (%)Age (years, medium, 95%CI)50, 39~6150, 33~640.0550, 40~6549, 34~620.1049, 39~6750, 31~640.03Stage T14588 (3.7)450 (52.8)0.7018(3.7)10 (6.9)0.03280 (10.5)450 (44.1)0.4672529157 (73.0)372 (43.7)118 (81.4)116 (80.0)635 (83.0)458 (44.9)38050 (23.3)30 (3.5)19 (13.1)19 (13.1)50 (6.5)113 (11.1)Stage N057137 (17.2)534 (62.7)1.04837 (17.2)32 (22.1)0.081310 (40.5)538 (52.7)0.2461596178 (82.8)318 (37.3)108 (81.4)113 (77.9)455 (59.5)483 (47.3)Grade1 and 252292 (42.8)430 (50.5)0.15477 (53.1)89 (61.4)0.168345 (45.1)493 (48.3)0.0643545123 (57.2)422 (49.5)68 (46.9)56 (38.6)420 (54.9)528 (51.7)ERNegative536142 (66.0)394 (46.2)0.40787 (60.0)68 (46.9)0.265386 (50.5)513 (50.2)0.004Positive53173 (34.0)458 (53.8)58 (40.0)77 (53.1)379 (49.5)508 (49.8)PRNegative649171 (79.5)478 (56.1)0.418108 (74.5)113 (77.9)0.081499 (65.2)625 (61.2)0.083Positive41844 (20.5)374 (43.9)37 (25.5)32 (22.1)266 (34.8)396 (38.8) Citation Format: Yang Hongjian, Xingfei Yu, Chen Wang, Zheng Yabing, Hu Jiejie, Xiying Shao, Liming Sheng, Juan Lin, Yuqin Ding, Haojun Xuan, Lijie Gong, Weiliang Feng, Chengdong Qin, Daobao Chen, Yang Yu. Preoperative systemic therapy versus upfront surgery in HER2-positive early breast cancer: A prospective nested case-control study in the real world [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS13-52.

This article examines how civilian defense militias shape violence during civil war. We define civilian defense forces as a sedentary and defensive form of pro-government militia that incumbents often use to harness the participation of civilians during a counterinsurgency campaign. We argue that civilian defense forces reduce the problem of insurgent identification. This leads to a reduction in state violence against civilians. However, we also claim that these actors undermine civilian support for insurgents, which leads to an increase in rebel violence against civilians and overall intensification of conflict. A statistical analysis of government and rebel violence against civilians from 1981 to 2005 and a qualitative assessment of a civilian defense force operating in Iraq from 2005 to 2009 offer strong support for our theoretical claims. These findings provide further insight into pro-government militias and their effects on violence. They also have wider ethical implications for the use of civilian collaborators during civil war.

State security forces have been locked in an ongoing struggle with the Communist Party of the Philippines – New People’s Army (NPA) for nearly fifty years. Over the course of the conflict, thousands of civilians across generations have taken up arms and participated in the counterinsurgency campaign. Citizen Armed Force Geographical Units (CAFGU) and other pro-government militias have played a key auxiliary role in combatting the insurgency and providing community security. This article draws on survey and interview data collected from CAFGU participants to examine the factors that influence decisions to join, as well as their implications for sustained participation and counterinsurgency strategy. Existing research on joining armed groups recognizes how environmental conditions, group processes, and individual motives interact to help explain participation. We shift our focus to the realm of the household and highlight how considerations related to that site affect participation. Our findings suggest that the need to avoid economic disaster and ensure a secure subsistence can have a notable influence on decisions to enlist and individual experiences as CAFGU. These effects, in turn, have implications for how the Philippine government carries out its counterinsurgency.

A growing line of research examines causes and consequences of militant group competition. However, empirical work on these topics has limitations. Most quantitative research uses relatively rough proxies for competition, such as counts of groups in a country. Other work uses dichotomous indicators, ignoring the intensity or degree of rivalries. Additionally, many studies examine either terrorist organizations or rebel groups, overlooking cross-type rivalry (e.g., terrorist vs. rebel). We address these issues by introducing time-varying dyadic rivalry data on hundreds of groups – rebels, terrorists, and pro-government militias – in Africa and Asia, 1990-2015. Rivalry levels include denouncements, threats, and violence. After presenting the data, we test the “outbidding” hypothesis: the notion that inter-organizational competition leads to more terrorism. This argument has found support in qualitative analyses, but quantitative tests using rivalry proxies show mixed results. Using our data we find support for the hypothesis. We conclude with research questions that could be addressed with the data.

AT THE TIME OF WRITING,1 hopes were high that a peace agreement would be signed between the Khartoum government and the Sudan People's Liberation Movement/Army (SPLM/A), bringing an end to a war in southern Sudan that has lasted on and off since independence in 1956. At the same time, there were worrying signs of growing conflict in the Darfur region in the west of the country, pitting forces based among the local Muslim peoples against pro-government militias known as the Janjaweed. The growth of this new conflict indicates that Sudan's civil war was never entirely a north-south or a Muslim-Christian struggle, but that it is a country-wide conflict that even incorporates other Muslim populations. The two main anti-government groupings in the Greater Darfur region are the Justice and Equality Movement (JEM) and the Sudanese Liberation Movement/Army (SLM/A). The Janjaweed militias are said to be largely of Chadian origin and finance themselves through plunder and pillage, reportedly enjoying implicit support from the government in Khartoum. The conflict has already left thousands of Darfurians killed, with an estimated 600,000 internally displaced and some 110,000 crossing as refugees into neighbouring Chad. As the government has denied access to most of the relief agencies operating in the country, the Darfur region is in effect sealed off from the outside world, leaving displaced people with little chance of receiving food aid and medical supplies. Despite its geographical remoteness, by late 2003 the crisis in Darfur gradually came to international attention. The grave deterioration of the situation during recent months has led Western supporters of the ongoing IGAD (Inter-Governmental Authority on Development) negotiations between the government of Sudan and the SPLM/A to acknowledge the seriousness of the escalating violence in Darfur. As the crisis is throwing a shadow over the peace talks in Naivasha in Kenya, the international community is expected to respond to the fighting. The insurrection in Darfur is gaining rapidly in coherence. In the light of the SPLM/A's bilateral talks with the government, several opposition movements are afraid that, once part of the transitional government, the

We compared the risk of hepatocellular carcinoma (HCC) development between patients with chronic hepatitis B (CHB) who achieved virological response (VR; HBV-DNA<2000IU/mL) with nucleos(t)ide analogues (NUCs) treatment (NUC-VR group) and patients with inactive CHB phase (ICHBP group). To adjust for imbalances between NUC-VR and ICHBP groups, propensity score matching (PSM) models with 1:1 ratios were performed. This study included 2032 patients (n=1291 in NUC-VR group and n=741 in ICHBP group). Before PSM, NUC-VR group was at higher risk of HCC development than ICHBP group at 7years (9.4% in NUC-VR group vs 3.3% in ICHBP group; P<0.001). However, after PSM, the cumulative HCC development rates at 7years were similar in NUC-VR and ICHBP groups using the three PSM models [2.0% vs 4.3%, PSM model-1 (612 pairs); 3.7% vs 4.4%, PSM model-2 (618 pairs); and 2.4% vs 4.3%, PSM model-3 (610 pairs)] (all P>0.05). After adjusting heavier hepatic fibrosis burden in NUC-VR group, overall clinical outcomes between 2 groups had become comparable. Therefore, if appropriate, NUCs to prevent viral replication and hepatic inflammation are required for achieving better prognosis.

Purpose To compare the multivariable-adjusted logistic regression model with the propensity score-matched, propensity score-stratified and propensity score-adjusted logistic regression models in estimating the effect of exposure to antidepressant agents in increasing the risk for type 2 diabetes mellitus. Methods A retrospective cohort study in the USA, using the Texas Medicaid prescription claims database was conducted from 1 January 1 2002 to 31 December 2009. Patients aged 18–64 years with new prescriptions for antidepressants (exposed group) or benzodiazepines (unexposed group) during the study period constituted the base population. Patients without diabetes at cohort entry were included in the study. Propensity scores, which predicted exposure to antidepressant agents, were used to create propensity score-matched, propensity score-stratified and propensity score-adjusted logistic regression models. Results A total of 44 715 patients formed the study sample. The risk estimates varied across different analytic methods. The propensity score-matched logistic regression model yielded the highest risk estimate (relative risk (RR) = 1.931; 95% confidence interval (CI): 1.705 to 2.187). The propensity score-stratified model (RR = 1.457; 95% CI: 1.127 to 1.884), the propensity score-adjusted regression model (RR = 1.491; 95% CI: 1.334 to 1.665) and the multivariable-adjusted logistic regression model (RR = 1.478; 95% CI: 1.323 to 1.653) yielded similar risk estimates. Conclusions Propensity score techniques using pharmacy claims data with a limited number of covariates yielded varied estimates of the treatment effect. The propensity score-matched model yielded a less biased treatment effect estimate than the multivariable-adjusted, the propensity score-stratified, and the propensity score-adjusted regression models.

Understanding Propensity Score Analyses

Introduction: Alcohol septal ablation (ASA) and septal myectomy (SM) are two options of septal reduction therapy (SRT) for patients with medication-resistant symptomatic obstructive hypertrophic cardiomyopathy (HCM). The 2020 AHA/ACC HCM Guideline recommends SM as the first-line choice and ASA as the second-line option to be conducted only if SM is contraindicated or surgical risk is high. However, little is known about the effectiveness of ASA versus SM for HCM on mortality in the real-world settings. Objective: To compare mortality between patients with HCM who underwent ASA and those who had SM using population-based databases. Methods: We identified patients with HCM who underwent an SRT from 2007 through 2014 using the SPARC database — a comprehensive, all-payer claims database that includes record of every inpatient stay and outpatient visit in New York State. We compared mortality at 15, 30, 180, and 360 days after SRT between the ASA group and the SM group (the reference group) using unadjusted analysis, propensity score matching (PSM), and inverse probability weighting (IPW). In the PSM and IPW models, we adjusted for age, sex, race/ethnicity, insurance type, and each item in the Elixhauser Comorbidity Index. Results: We identified 755 patients with HCM who underwent an SRT, including 348 in the ASA group and 407 in the SM group. In the unadjusted analysis, mortality in the ASA group was lower than that in the SM group (crude mortality at 360 days, 3.7% vs. 7.4%; Figure ). Using the PSM method, mortality was lower in the ASA group in the 180-day and 360-day post-SRT periods (adjusted odds ratio [aOR] = 0.31 at 360 days; 95% confidence interval [CI], 0.09-0.93; P = 0.049). The IPW model showed consistent findings with the PSM model (aOR = 0.44 at 360 days; 95% CI, 0.21-0.88; P = 0.02). Conclusions: Patients with HCM who underwent ASA had lower mortality than those who had SM during a 1-year post-SRT period in this population-based study.

The research expects to give full play to the role of venture capital in corporate innovation and enhance the development capability of enterprises. Based on Propensity Score Matching (PSM) model, the characteristics of venture capital and startup enterprises are analyzed, and the innovation of venture capital is discussed. Next, the PSM model is used to analyze the innovation of venture capital intervention in enterprises from risk probability intervention, probability evaluation, matching equilibrium validity test, matching results analysis, different venture capital, and different background risks. The results show that the difference of standardized mean is close to 0, which accords with the equilibrium test. The significant impact of venture capital intervention on the Number of Invention Patent Applications (NIPA) and Number of Utility Model Patent Applications (NUMPA) is 0.1 and 0.01, respectively. Venture capital intervention has a significantly positive impact on NIPA and NUMPA but has no significant positive impact on Number of Design Patent Applications (NDPA). The impact of joint venture capital intervention on the NIPA, NUMPA, and NDPA is 0.0874, 0.0635, and 0.1213, respectively. Hence, the intervention of joint venture capital can greatly promote the increase of Number of Patent Applications (NPA), especially, NIPA, and NUMPA. Compared with private venture capital, joint venture capital plays a greater role in promoting the growth of NPA and NIPA. Compared with private venture capital and foreign venture capital, national venture capital has a stronger innovation orientation and a longer investment cycle, which can greatly improve innovation performance, such as NIPA, while private venture capital and foreign venture capital have a less significant impact on enterprise innovation performance. The results demonstrate that the foreign capital sharing assessment based on the PSM model can be a good predictor of the performance of startups. It is hoped that the research results can provide a reference for the development of startups.