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Many studies have analysed what could motivate centre-right governments to develop progressive family policies, given their historically traditionalist ideology. Updating classic institutionalist accounts, this article expands the focus beyond centre-right parties formally in charge. It argues that in coalition and minority governments, partisan veto players may act as agenda-setters, design policy reforms and successfully exert pressure to approve them through three mechanisms: agreements for government formation, conditions for government survival and bureaucratic continuity. Drawing on novel empirical data from interviews and document analysis, this article applies deductive process tracing to analyse the German parental allowance reform of 2006 and the Spanish 2017 paternity leave extension. The findings complement existing studies that focus on the agency of centre-right parties as ‘protagonists’ of these reforms, arguing that in some cases they have instead ‘consented’ to reforms proposed and supported by other parties.
Co-management regimes are institutional innovations that hold the promise of achieving sustainable common-pool resource governance. However, the transition to such institutional regimes in coastal resource systems has faced challenges in many countries. This article examines the processes and outcomes of such institutional changes in coastal fisheries in Ghana, where the transition to co-management was unsuccessful. Combining theoretical perspectives from legal pluralism in legal anthropology and ideational theories of institutional change within institutional economics, the paper uses process tracing to examine the role of ideology and historical institutional dynamics of the resource context in the institutionalization and failure of co-management arrangements for governing coastal fisheries. The study finds that ideological conflicts and historical legacies of legal pluralism hindered the practice and outcomes of coastal fisheries co-management in Ghana. The article argues for particular attention to the historical institutional dimensions and underlying worldviews of the resource context in institutional interventions for sustainability in coastal resource systems.
Due to high turnover, formal international organizations (FIGOs) face challenges in retaining knowledge – particularly about strategic errors in operations. Errors in the arena of crisis management involve high costs, such as civilian casualties. However, scholarship addressing how security FIGOs share knowledge about what went wrong remains limited. This chapter argues that informal networks among political and military elites are critical for knowledge sharing within FIGOs, even in the face of sophisticated formal learning systems. The study draws on interviews with 120 elite officials at NATO and employs process tracing and social network analysis. Findings indicate that knowledge sharing hinges on the actions of a few elites – “knowledge guardians” – who are central to the transnational, informal elite network. Challenging assumptions about the superiority of formal systems, this chapter stresses that informal governance plays a central role in FIGO knowledge retention, which is critical for institutional memory and learning.
The retrieval of past instances stored in memory can guide inferential choices and judgments. Yet, little process-level evidence exists that would allow a similar conclusion for preferential judgments. Recent research suggests that eye movements can trace information search in memory. During retrieval, people gaze at spatial locations associated with relevant information, even if the information is no longer present (the so-called ‘looking-at-nothing’ behavior). We examined eye movements based on the looking-at-nothing behavior to explore memory retrieval in inferential and preferential judgments. In Experiment 1, participants assessed their preference for smoothies with different ingredients, while the other half gauged another person’s preference. In Experiment 2, all participants made preferential judgments with or without instructions to respond as consistently as possible. People looked at exemplar locations in both inferential and preferential judgments, and both with and without consistency instructions. Eye movements to similar training exemplars predicted test judgments but not eye movements to dissimilar exemplars. These results suggest that people retrieve exemplar information in preferential judgments but that retrieval processes are not the sole determinant of judgments.
We connect the literature on causal models to qualitative inference strategies used in process tracing. The chapter outlines a procedure for drawing case-level causal inferences from a causal model and within-case evidence. We also show how a key result from the causal-models literature provides a condition for when the observation of a node in a causal model (a “clue”) may be (or certainly will not be) informative, and we extract a set of implications for process-tracing methods.
We apply the causal-model-based approach to process tracing to two major substantive issues in comparative politics: the relationship between inequality and democratization and the relationship between institutions and growth. Drawing on case-level data, we use qualitative restrictions on causal types together with flat priors to draw inferences about a range of causal queries. The applications illustrate the different types of learning that can be gleaned from information on moderators and mediators, as well as the scope for learning from historical data when researchers have informative beliefs about confounding processes.
This chapter argues for the utility of causal models as a framework for choosing research strategies and drawing causal inferences. It provides a roadmap for the rest of the book. The chapter highlights the approach’s payoffs for qualitative analysis, for combining intensive and extensive empirical strategies, and for making research design choices.
This chapter is the first of three in which we investigate how causal models can inform research design. In this chapter, we draw out the implications of the causal-model approach for clue-selection strategies, for figuring out which pieces of evidence are likely to be most informative about a question of interest. We demonstrate procedures for assessing which clues minimize expected posterior variance and how to construct an optimal decision tree for determining a dynamic clue-gathering strategy.
This chapter traces the complex trajectory of land tenure reforms in Benin since the democratic transition and liberalisation of the economy in the early 1990s. It shows that conceptions of the problem of land tenure insecurity and the responses to it have often clashed. Attention paid to sectors (rural vs urban) has varied as well as the timing and the nature of land tenure reforms. The solution of formal land titling propounded by international donor and local supporters has been considered by many as both inaccessible and unsuited to the needs of the majority of the population, hence the search for legal and institutional alternatives. This history of land reforms reveals intricate conflicts involving corporatist struggles, conflicts of interest between different stakeholders, and divergent social choices. It highlights the political economy dimension of land tenure problems and their instrumentalisation by some actors and competing public policy networks, the strengths and limitations of attempts to implement policy reforms, and the influence of donors in reform processes. It also questions the capacity of the intended reforms to modify practices and have enough inclusiveness.
There is a growing consensus in the social sciences on the virtues of research strategies that combine quantitative with qualitative tools of inference. Integrated Inferences develops a framework for using causal models and Bayesian updating for qualitative and mixed-methods research. By making, updating, and querying causal models, researchers are able to integrate information from different data sources while connecting theory and empirics in a far more systematic and transparent manner than standard qualitative and quantitative approaches allow. This book provides an introduction to fundamental principles of causal inference and Bayesian updating and shows how these tools can be used to implement and justify inferences using within-case (process tracing) evidence, correlational patterns across many cases, or a mix of the two. The authors also demonstrate how causal models can guide research design, informing choices about which cases, observations, and mixes of methods will be most useful for addressing any given question.
Edited by
David Weisburd, Hebrew University of Jerusalem and George Mason University, Virginia,Tal Jonathan-Zamir, Hebrew University of Jerusalem,Gali Perry, Hebrew University of Jerusalem,Badi Hasisi, Hebrew University of Jerusalem
The 2018 National Academy of Sciences report on proactive policing acknowledges that police strategies to prevent crime are likely to have collateral consequences on community outcomes, and in some cases (such as community-oriented policing) aim to shape community outcomes directly. However, strategies that effectively prevent crime have mixed effects on community outcomes, while approaches that improve community perceptions of the police often do not have strong crime control benefits. In this chapter I propose that the future of proactive policing may depend on developing a better understanding of the complex relationship between communities, police, and crime prevention. Rather than viewing community impacts and crime prevention impacts as two separate processes, I argue that community support and collaboration are inherent to proactivity and may ultimately moderate the success or failure of proactive policing strategies. I conclude with suggestions for future research and theory development to better understand this relationship and translate research into effective practice.
This chapter introduces computational models of decision making as worthy successors to the traditional, algebraic utility framework that has dominated the field. It provides an overview of several different computational modeling approaches before providing a detailed example of perhaps the most well-established of these, based on sequential sampling of information and evidence accumulation. It is shown how this approach can account for common paradoxes in decision behavior, and how it can be extended to a variety of tasks and response modes while retaining the same basic cognitive principles. The chapter concludes with an illustration of how process-tracing methods that capture the information acquisition and response processes can help to evaluate computational models of decision making and discriminate among them.
A steadily increasing number of European countries recently adopted their own ‘Africa policies’. The temporal and geographical clustering of such plans suggests that a policy diffusion process might have been at play, with the introduction and the shape of a policy in a given country being influenced by those of other countries. This paper tests the policy diffusion hypothesis through an in-depth analysis of the case of Italy, a country that in recent times stepped up substantially its engagement with sub-Saharan Africa. Tracing the origins and features of Rome's policy towards the region, however, shows that external influences were much more limited than expected. It was primarily two country-specific drivers – namely, the enduring effects of the European debt crisis on the Italian economy and a sudden and massive, if temporary, increase in irregular migration – which pushed Italy towards Africa and shaped its approach. The paper thus sheds light on how the marked resemblance of policies almost contemporaneously adopted by distinct EU member states – that is, a tight succession and a highly interconnected environment strongly pointing at cross-country influences – can hide motives and processes that are actually highly specific to each of them and essentially by-pass policy diffusion dynamics.
Chapter 1 begins with the story of the 2015 La Línea customs fraud scandal and its connections to the criminal structures mounted by military intelligence at the height of the 36-year civil war. Drawing on this illustrative example, the chapter reframes debates on post-conflict statebuilding and puts forward a novel argument about how counterinsurgent elites introduce institutional innovations that undermine core state activities. It further lays out the key theoretical contributions of the book, specifically as they relate to war and state formation and post-conflict peacebuilding and reconstruction. The chapter also introduces the Central American context and explains why it is a fruitful setting in which to explore the institutional legacies of civil war. It then discusses the book’s methodology and the unique archival and interview sources of data.
The aim of this article is to evaluate the contribution of process tracing data to the development and testing of models of judgment and decision making (JDM). We draw on our experience of editing the “Handbook of process tracing methods for decision research” recently published in the SJDM series. After a brief introduction we first describe classic process tracing methods (thinking aloud, Mouselab, eye-tracking). Then we present a series of examples of how each of these techniques has made important contributions to the development and testing of process models of JDM. We discuss the issue of large data volumes resulting from process tracing and remedies for handling those. Finally, we argue for the importance of formulating process hypotheses and opt for a multi-method approach that focuses on the cross-validation of findings.
In two studies on mobile phone purchase decisions, we investigated consumers’ decision strategies with a newly developed process tracing tool called InterActive Process Tracing (IAPT). This tool is a combination of several process tracing techniques (Active Information Search, Mouselab, and retrospective verbal protocol). After repeatedly choosing one of four mobile phones, participants formalized their strategy so that it could be used to make choices for them. The choices made by the identified strategies correctly predicted the observed choices in 73% (Experiment 1) and 67% (Experiment 2) of the cases. Moreover, in Experiment 2 we directly compared Mouselab and eye tracking with respect to their impact on information search and strategy description. We found only minor differences between these two methods. We conclude that IAPT is a useful research tool to identify choice strategies, and that using eye tracking technology did not increase its validity beyond that gained with Mouselab.
The translation of choice attributes into more meaningful information (e.g., from kWh to costs) is a form of choice architecture that is thought to facilitate decision making by providing decision signposts that activate personally relevant but latent objectives and guide decisions towards options that are most congruent with the activated objectives. Here, we investigated the psychological mechanisms that underlie and drive the directional effects of attribute translations on decision making. Across two choice experiments (total N = 973), we provide empirical support for our proposition that attribute translations operate via pre-decisional attention processes. Specifically, we demonstrate that attribute translations focus individuals’ attention on choice options that are most congruent with the concerns highlighted by translations, and that this attentional prioritization of alternatives predicts choice. In addition to the cognitive mechanisms underlying attribute translations, we highlight the choice architectural principles that moderate the effectiveness of translations. We show that the directional effects of attribute translations are driven by the information that translations provide rather than by contextual changes in the decision environment. In line with previous research on evaluability, we find the effectiveness of attribute translations to depend on information format, with translations conveying evaluative information having a larger impact on decision making than translations providing numerical information. The present study is among the first to investigate the decision making processes underlying a choice architectural intervention. It provides insights into the mechanisms that drive and facilitate the signpost effect and renders recommendations for the implementation of attribute translations in policy making.
It is a widely held view that people rely on incomplete information to find a relationship partner, resulting in non-compensatory choice heuristics. However, recent experimental work typically finds that partner choice follows compensatory choice strategies. To bridge this gap between theory and experimental evidence, we characterize the mate choice problem by distinguishing the information search process from the evaluation process. In an eye-tracking experiment and a MouseLab experiment, we show that people display strong value-directed search heuristics in response to all types of cues and that the magnitude of value-directed searches increases with cue primacy. Cue primacy also explains the interaction effect of cue type and participant sex on the extent of valued-directed search. We further argue that value-directed searching does not necessarily lead to non-compensatory choice rules but may serve compensatory decision-making. Our results demonstrate that people may adopt remarkably smart search heuristics to find an ideal partner efficiently.
Previous research has shown that interruptions can lead to delays and errors on the interrupted task. Such research, however, seldom considers whether interruptions cause a change in how information is processed. The central question of this research is to determine whether an interruption causes a processing change. We investigate this question in a decision-making paradigm well-suited for examining the decision-making process. Participants are asked to select from a set of risky gambles, each with multiple possible stochastic outcomes. The information gathering process is measured using a mouse-click paradigm. Consistent with past work, interruptions did incur a cost: An interruption increased the time and the amount of information needed to make a decision. Furthermore, after an interruption, participants did seem to partially “restart” the task. Importantly, however, there was no evidence that the information gathering pattern was changed by an interruption. There was also no overall cost to the interruption in terms of choice outcome. These results are consistent with the idea that participants recall a subset of pre-interruption information, which was then incorporated into post-interruption processing.
Currently, a disparity exists between the process-level models decision researchers use to describe and predict decision behavior and the methods implemented and metrics collected to test these models. The current work seeks to remedy this disparity by combining the advantages of work in decision research (mouse-tracing paradigms with contingent information display) and cognitive psychology (eye-tracking paradigms from reading and scene perception). In particular, we introduce a new decision moving-window paradigm that presents stimulus information contingent on eye fixations. We provide data from the first application of this method to risky decision making, and show how it compares to basic eye-tracking and mouse-tracing methods. We also enumerate the practical, theoretical, and analytic advantages this method offers above and beyond both mouse-tracing with occlusion and basic eye tracking of information without occlusion. We include the use of new metrics that offer more precision than those typically calculated on mouse-tracing data as well as those not possible or feasible within the mouse-tracing paradigm.