Between Replication and Docking: "Adaptive Agents, Political Institutions, and Civic Traditions" Revisited

This article has two primary objectives: (i) to replicate an agent-based model of social interaction by Bhavnani (2003), in which the author explicitly specifies mechanisms underpinning Robert Putnam\'s (1993) work on Civic Traditions in Modern Italy, bridging the gap between the study\'s historical starting point—political regimes that characterized 14th Century Italy—and contemporary levels of social capital—reflected in a \'civic\' North and an \'un-civic\' South; and (ii) to extend the original analysis, using a landscape of Italy that accounts for population density. The replication exercise is performed by different authors using an entirely distinct ABM toolkit (PS-I) with its own rule set governing agent-interaction and cultural change. The extension, which more closely approximates a docking exercise, utilizes equal area cartograms otherwise known as density-equalizing maps (Gastner and Newman 2004) to resize the territory according to 1993 population estimates. Our results indicate that: (i) using the criterion of distributional equivalence, we experience mixed success in replicating the original model given our inability to restrict the selection of partners to \'eligible\' neighbors and limit the number of agent interactions in a timestep; (ii) increasing the number of agents and introducing more realistic population distributions in our extension of the replication model increases distributional equivalence; (iii) using the weaker criteria of relational alignment, both the replication model and its extension capture the basic relationship between institutional effectiveness and civic change, the effect of open boundaries, historical shocks, and path dependence; and (iv) that replication and docking may be usefully combined in model-to-model analysis, with an eye towards verification, reimplementation, and alignment.Replication, Docking, Agent-Based Model, Italy, Social Capital

REsCape: an Agent-Based Framework for Modeling Resources, Ethnicity, and Conflict

This research note provides a general introduction to REsCape: an agent-based computational framework for studying the relationship between natural resources, ethnicity, and civil war. By permitting the user to specify: (i) different resource profiles ranging from a purely agrarian economy to one based on the artisanal or industrial extraction of alluvial or kimberlite diamonds; (ii) different patterns of ethnic domination, ethnic polarization, and varying degrees of ethnic salience; as well as (iii) specific modes of play for key agents, the framework can be used to assess the effects of key variables — whether taken in isolation or in various combinations — on the onset and duration of civil war. Our objective is to make REsCape available as an open source toolkit in the future, one that can be used, modified, and refined by students and scholars of civil war.Agent-Based Model, Ethnicity, Salience, Polarization, Domination, Civil War, Greed, Natural Resources

Drivers of COVID-19 protest across localities in Israel: a machine-learning approach

Anti-government protests emerged globally in response to COVID-19 countermeasures. What are the key drivers of these pandemic-related protests, and to what extent do they differ from the drivers of non-COVID protests? We examine these questions in the context of Israel, which faced a growing political crisis at the start of the pandemic, effectively blurring the distinction between different causes of protest. Our data features 1,922 protests across 189 Israeli localities for the period between March and July 2022. Using a machine learning approach, we find that all protests, regardless of whether they were directly related to the pandemic or not, were motivated by the same set of key indicators – albeit with the ranking of drivers for COVID-related protests inverted for non-COVID protests. Local infection rates and government responses were more pronounced for the former, whereas differences in residential and commercial property taxes, access to affordable housing, quality of education and demography were among the most important drivers for the latter. Our analysis underscores the role that local governments played in managing the pandemic, and demonstrates that variation in socioeconomic conditions had an important effect on the incidence of protests across Israel

Trajectories of resilience to acute malnutrition in the Kenyan drylands

IntroductionInsight into the resilience of local food systems—variability driven by climate, conflict, and food price shocks—is critical for the treatment and prevention of child acute malnutrition.MethodsWe use a combination of latent class mixed modeling and time-to-event analysis to develop and test a measure of resilience that is outcome-based, sensitive to specific shocks and stressors, and captures the enduring effects of how frequently and severely children face the risk of acute malnutrition.ResultsHarnessing a high-resolution longitudinal dataset with anthropometric information on 5,597 Kenyan households for the 2016–20 period, we identify resilience trajectories for 141 wards across Kenya. These trajectories—characterized by variation in the duration and severity of episodes of acute malnutrition—are associated with differential risk: (1) some 57% of wards exhibit an increasing trajectory—high household risk despite growing resilience; (2) 39% exhibit chronic characteristics—showing no real signs of recovery after an episode of crisis; (3) 3% exhibit robust characteristics—low variability with low-levels of individual household risk; whereas (4) 1% show a steady decrease in resilience—associated with high levels household risk.DiscussionOur findings highlight the importance of measuring resilience at the ward-level in order to better understand variation in the nutritional status of rural households

How does the geography of surveillance affect collective action?

How does residing in the proximity of surveillance infrastructure—i.e., checkpoints, the separation barrier, and military installations—affect support for cooperative and confrontational forms of collective action? Cooperative actions involve engagement with outgroups to advance the ingroup cause (e.g., negotiations, joint actions, and peace movements), whereas confrontational actions involve unilateral tactics to weaken the outgroup (e.g., boycott, armed resistance). In the context of West Bank and Jerusalem, we combine geo‐coded data on the surveillance infrastructure with a representative survey of the adult population from 49 communities (N = 1,000). Our multilevel analyses show that surveillance does not affect support for confrontational actions but instead decreases support for cooperative actions. Moreover, we identify a new, community‐level mechanism whereby surveillance undermines cooperative actions through weakening inclusive norms that challenge dominant us‐versus‐them perspectives. These effects are empirically robust to various individual‐ and community‐level controls, as well as to the potential of reverse causality and residential self‐selection. Our findings illustrate how cooperative voices and the fabric of social communities become the first casualties of exposure to surveillance. They also speak to the importance of considering structural factors, with broader implications for the socio‐psychological study of collective action

Household behavior and vulnerability to acute malnutrition in Kenya

Anticipating those most at-risk of being acutely malnourished significantly shapes decisions that pertain to resource allocation and intervention in times of food crises. Yet, the assumption that household behavior in times of crisis is homogeneous—that households share the same capacity to adapt to external shocks—ostensibly prevails. This assumption fails to explain why, in a given geographical context, some households remain more vulnerable to acute malnutrition relative to others, and why a given risk factor may have a differential effect across households? In an effort to explore how variation in household behavior influences vulnerability to malnutrition, we use a unique household dataset that spans 23 Kenyan counties from 2016 to 2020 to seed, calibrate, and validate an evidence-driven computational model. We use the model to conduct a series of counterfactual experiments on the relationship between household adaptive capacity and vulnerability to acute malnutrition. Our findings suggest that households are differently impacted by given risk factors, with the most vulnerable households typically being the least adaptive. These findings further underscore the salience of household adaptive capacity, in particular, that adaption is less effective for economic vis-à-vis climate shocks. By making explicit the link between patterns of household behavior and vulnerability in the short- to medium-term, we underscore the need for famine early warning to better account for variation in household-level behavior

Adaptive Agents, Political Institutions and Civic Traditions in Modern Italy

Long duration historical studies have been formative in shaping comparative analysis. Yet historical processes are notoriously difficult to study, and their findings equally difficult to validate empirically. In this paper, I take Robert Putnam’s work on Civic Traditions in Modern Italy and attempt to bridge the gap between the study’s historical starting point and contemporary observations, using an agent-based model of social interaction. My use of a computational model to study historical processes—in this case the inculcation and spread of social capital—supports Putnam's claim of path dependence. Moving beyond Putnam’s study, my results indicate that the formation of civic (or uncivic) communities is not deterministic, that their emergence is sensitive to historical shocks, and that the absence of political boundaries lowers aggregate levels of civicness in regions characterized by effective institutions. In addition, the simulation suggests that minor improvement to ineffective institutions—making them moderately effective—constitute a mid-level equilibrium trap with the least desirable social consequences.Social Capital, Italy, Agent-Based Model

Ethnic Minority Rule and Civil War Onset How Identity Salience, Fiscal Policy, and Natural Resource Profiles Moderate Outcomes

Using an agent-based computational framework designed to explore the incidence of conflict between two nominally rival ethnic groups, we demonstrate that the impact of ethnic minority rule on civil war onset could be more nuanced than posited in the literature. By testing the effects of three key moderating variables on ethnic minority rule, our analysis demonstrates that: (i) when ethnicity is assumed to be salient for all individuals, conflict onset increases with size of the minority in power, although when salience is permitted to vary, onset decreases as minority and majority approach parity; (ii) fiscal policy—the spending and investment decisions of the minority EGIP—moderates conflict; conflict decreases when leaders make sound decisions, increases under corrupt regimes, and peaks under ethno-nationalist regimes that place a premium on territorial conquest; and lastly (iii) natural resources—their type and distribution—affect the level of conflict which is lowest in agrarian economies, higher in the presence of lootable resources, and still higher when lootable resource are “diffuseâ€. Our analysis generates a set of propositions to be tested empirically, subject to data availability.agent-based modeling; civil war; ethnic minority rule; political exclusion