Search Results

This chapter examines how the qualitative and quantitative research traditions treat within-case analysis versus cross-case analysis for causal inference. In qualitative research, the primary focus is on specific events and processes taking place within each individual case. Leading qualitative methodologies of hypothesis testing, such as process tracing and counterfactual analysis, are fundamentally methods of within-case analysis. By contrast, quantitative research traditionally involves exclusively cross-case comparison. The chapter begins with a comparison of the typical roles (or nonroles) of within-case and cross-case analysis in case studies versus experiments. It then considers how causal inference in quantitative and qualitative research is linked to the use of “data-set observations” and “causal-process observations,” respectively. It also explains the differences between process-tracing tests and statistical tests and concludes by suggesting that cross-case analysis and within-case analysis can and often should be combined.

This chapter examines the use of counterfactual analysis in making causal inferences in the qualitative and quantitative research paradigms. To assess a counterfactual claim about a particular case, the typical approach is to conduct a within-case analysis of that case. Qualitative researchers formulate counterfactuals that are “conceivable,” in the sense that imagining that a cause had not occurred (or occurred differently) does not require fundamentally rewriting history. By contrast, quantitative scholars use counterfactuals mainly to illustrate a general causal model. The chapter first considers the Fundamental Problem of Causal Inference, which is the problem of a counterfactual, before discussing the statistical approach to counterfactuals. In particular, it describes the “minimum rewrite” rule. It suggests that counterfactual analyses are an important mode of causal inference within the qualitative tradition, but not commonly used within the quantitative tradition.

This chapter examines how the qualitative and quantitative research traditions empirically assess theories about mechanisms when making causal inferences. In the qualitative paradigm, researchers carry out this assessment by attempting to observe causal mechanisms through process tracing and through the analysis of causal-process observations. In the qualitative paradigm, the within-case analysis of specific cases is combined with the effort to observe mechanisms. By contrast, statistical methods are not designed to observe mechanisms within particular cases. The chapter considers the importance of mechanisms in causal inference as well as the use of process tracing in multimethod vs. qualitative research. It shows that multimethod research, which integrates regression and case study analysis, is increasingly regarded as a best practice.

This chapter examines two approaches used in social science research: the “causes-of-effects” approach and the “effects-of-causes” approach. The quantitative and qualitative cultures differ in the extent to which and the ways in which they address causes-of-effects and effects-of-causes questions. Quantitative scholars, who favor the effects-of-causes approach, focus on estimating the average effects of particular variables within populations or samples. By contrast, qualitative scholars employ individual case analysis to explain outcomes as well as the effects of particular causal factors. The chapter first considers the type of research question addressed by both quantitative and qualitative researchers before discussing the use of within-case analysis by the latter to investigate individual cases versus cross-case analysis by the former to elucidate central tendencies in populations. It also describes the complementarities between qualitative and quantitative research that make mixed-method research possible.

This chapter compares two causal models used in qualitative and quantitative research: an additive-linear model and a set-theoretic model. The additive-linear causal model is common in the statistical culture, whereas the set-theoretic model is often used (implicitly) in the qualitative culture. After providing an overview of the two causal models, the chapter considers the main differences between them. It then gives an example to illustrate how a set-theoretic causal model is implicitly used in the within-case analysis of a specific outcome. It also explains how the form of causal complexity varies across the quantitative and qualitative paradigms. Finally, it examines another difference between the causal models used in quantitative and qualitative research, one that revolves around the concept of “equifinality” or “multiple causation.” The chapter suggests that while the two causal models are quite different, neither is a priori correct.

This chapter presents a cross-case analysis of the case studies discussed in Chapters 3–7. A cross-case analysis provides further insights into the relevance and strength of factors in any causal scheme — something of which the analytical frameworks could only provide limited prior understandings. This process also enables a further testing of the relevance, and a potential deepening, of the analytical frameworks themselves and the insights they can bring to bear in future studies of the phenomena. Three patterns emerge that characterize relationship arrangements as inefficient, adequate, or efficient. Xerox, British Aerospace, and Inland Revenue's arrangements were found generally to be inefficient in the first few years, raising serious doubts over whether the relationship arrangements offered operational advantages or benefits over the previous in-house operations. Subsequently, all three sets of arrangements were improved to a more than adequate level. BPX's arrangements described an overall adequate arrangement in terms of relational efficiency, even though the Alliance approach generally proved operationally ineffective. Finally, after a bad start, ESSO's arrangement showed the nearest to what could be termed relationally efficient, although certain practices (e.g. contract renewal) do introduce considerable transaction costs. The ideal scenario in terms of efficiency would be low results on all three accounts.

This chapter begins with a discussion of psychometric aspects of neuropsychological tests. It then discusses the classical test theory model, criterion-referenced testing, probabilistic test models, individual case classification, psychometric single-case analysis, and comparison of a single case to a small control or normative sample.

This chapter demonstrates the main points of all other chapters by means of a thorough analysis of the European Court of Human Rights’ decision in Otto-Preminger Institut v Austria, a case concerning Art. 10 of the Convention. The conflict is between the freedom of expression and the freedom of religion. It is demonstrated in detail how proportionality analysis works in this case. Numerous mistakes and insufficiencies in the Court’s reasoning are identified. It is argued that a proper proportionality analysis may have a rationalizing effect on legal reasoning.

For four cases of prolonged research misconduct over a decade or more, undetected by peer review, replication, coauthors or institutional oversight, are described. Several of these cases also involved human subjects protection violations which, if properly investigated, would have revealed the misconduct. Citation to fabricated/falsified studies continued for years and tracing harm to subjects or eventual patients rarely addressed. Charges of research misconduct can also be used to stop or slow a competitor's program of research or be used by a company whose product sales would be damaged by the research findings. Ongoing and cumulative analysis of research misconduct cases offers lessons learned.

Chapter 4 of Practice Research in the Human Services: A University-Agency Partnership Model offers examples of practice research that employ cross-case comparisons in order to identify practice implications and enable senior managers to identify innovations for application to their own organizations. The key steps are described, including the dialogue and negotiation process that involves the university researcher with the practice community of agency administrators. The first study described in the chapter examined welfare reform implementation by county agencies, based on interviews with social service agency staff and consumers, as well as documents relevant to each program or practice. The second study focused on organizational knowledge-sharing processes in county agencies, while the third study explored organizational growth and resilience among nonprofit organizations. Practice research principles generated by the projects relate to generalizability limitations, data source triangulation and timeliness, and case study context.

Children’s participation in all matters that concern them, particularly child protection decision-making, have many positive effects on children. It is also their right granted by the United Nations Convention on the Rights of the Child. However, in child protection practice there are many obstacles to including children in decision-making processes. First, the article reviews the policy and public discourse in England, Germany, and the Netherlands regarding children’s participation in investigations into suspected child maltreatment. Second, an analysis of 1,207 case files of investigations into suspected child maltreatment unfolds the extent of children’s participation and factors associated with participation within the three countries. Although all three countries grant the right to participate in decision-making to children, documented participation in child protection decision-making is very low even when older children are considered. Children’s participation in decision-making is closely linked to caretakers’ participation in decision-making. Thus, children are almost never included in decision-making when their caretaker is not. Children’s participation is associated with a higher likelihood for individual support for children in the Netherlands and Germany. The results point to the need for research on barriers of children’s participation as well as the need to provide more resources for case workers to be able to facilitate children’s participation.

Missing data are ubiquitous in ecological and evolutionary data sets as in any other branch of science. The common methods used to deal with missing data are to delete cases containing missing data, and to use the mean to fill in missing values. However, these ‘traditional’ methods will result in biased estimation of parameters and uncertainty, and reduction in statistical power. Now, better missing data procedures such as multiple imputation and data augmentation are readily available and implementable. This chapter introduces the basics of missing data theory—most importantly, the three missing data mechanisms: missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR); the chapter also explains relevant concepts of importance such as EM algorithms and MCMC procedures. This chapter enables the application of proper missing data procedures, in particular multiple imputation, using R packages.

In this chapter, the critical-contextualist approach is applied to a case study in which the findings of three expert committee reports on the possible links between diet and health are analyzed. Such committee reports sponsored by the National Academy of Sciences (NAS) are helpful in explaining the cogency of scientific argumentation. This case analysis, by using different source materials and argumentation-theoretic tools, highlights three directions of normative concern on the part of participants. These directions include the content of the reports, the quality of the committee transactions, and the public merits of the reports. The chapter concludes with the discussion of tensions in the rhetorical use of process ideals that are identified after examining the debates surrounding the reports and NAS procedures.

This chapter looks at the cases and projects presented in this book, comparing and contrasting them. It uses the ‘sensitizing concepts’ introduced in Chapter 2, partially further developing them in order to arrive at a more nuanced understanding of the conditions for achieving a sustainable outcome and the strategies researchers assume. Another objective is to capture aspects that ‘matter for design’ in support of sustainable outcomes: more specifically, to learn how to set up a project or research line, how to create alliances in support of sustainability, and how to arrange for future-proofing activities well before a project ends. Key findings in this chapter relate to the usefulness of thinking about different forms of sustainability, the importance of temporal issues, the tedious and often unaccounted-for work of contextualizing, the relationship between ownership, appropriation, and learning processes, and the relevance of the innovation scenario a research line follows.

This chapter weaves together excerpts from the supreme court judge interviews, discourse instances of oral arguments, and coding of selected features from the court exchanges to illuminate the discursive character of oral argument. Described is a challenge that judges face both to be outside of culture and demographic categories, and, at the same time, to bring their experience and unique cultural identities to their judging. A deviant case, one instance out of the 35 exchanges between attorneys and the justices, is described in which the genre of oral argument was enacted in a markedly different style. For this deviant case, the chapter suggests what identity was accomplished for the focal attorney by his and the Court’s use of non-typical discourse moves.

Computer science and physics have been closely linked since the birth of modern computing. This book is about that link. John von Neumann’s original design for digital computing in the 1940s was motivated by applications in ballistics and hydrodynamics, and his model still underlies today’s hardware architectures. Within several years of the invention of the first digital computers, the Monte Carlo method was developed, putting these devices to work simulating natural processes using the principles of statistical physics. It is difficult to imagine how computing might have evolved without the physical insights that nurtured it. It is impossible to imagine how physics would have evolved without computation. While digital computers quickly became indispensable, a true theoretical understanding of the efficiency of the computation process did not occur until twenty years later. In 1965, Hartmanis and Stearns [227] as well as Edmonds [139, 140] articulated the notion of computational complexity, categorizing algorithms according to how rapidly their time and space requirements grow with input size. The qualitative distinctions that computational complexity draws between algorithms form the foundation of theoretical computer science. Chief among these distinctions is that of polynomial versus exponential time. A combinatorial problem belongs in the complexity class P (polynomial time) if there exists an algorithm guaranteeing a solution in a computation time, or number of elementary steps of the algorithm, that grows at most polynomially with input size. Loosely speaking, such problems are considered computationally feasible. An example might be sorting a list of n numbers: even a particularly naive and inefficient algorithm for this will run in a number of steps that grows as O(n2), and so sorting is in the class P. A problem belongs in the complexity class NP (non-deterministic polynomial time) if it is merely possible to test, in polynomial time, whether a specific presumed solution is correct. Of course, P ⊆ NP: for any problem whose solution can be found in polynomial time, one can surely verify the validity of a presumed solution in polynomial time.

This book deals with human rights action planning from theoretical, doctrinal, empirical, and practical perspectives. It is structured into four parts and seven chapters. The first part is composed of two chapters that advance a novel general theory of human rights planning including four sub-theories. The second part, which contains two chapters, presents the results of a content analysis of all the nine core human rights conventions revealing the scope and nature of the obligation of the states to adopt a plan of action for implementing human rights. The third part, including one chapter, provides the empirical findings of a cross-case analysis of national human rights action plans of fifty-three countries exploring the major problems of these plans in different phases of planning and uncovering the underlying causes of these problems. The last part, which consists of two chapters, examines both national and supra-national human rights governance, setting out how these plans should be best developed, implemented, monitored, and how to maximize their effectiveness both at the national and international level.

This chapter considers a number of reasons to reflect on how breast cancer is understood in Western medicine. These include that breast cancer serves as a prominent nosology and nosography in medicine which affects a significant number of women, commands a large portion of financial resources, serves as the focus of numerous policies and laws, provides a glimpse into history, calls out for clarification, and carries ethical implications. In the analysis, breast cancer offers a case study in philosophy of medicine for purposes of asking questions about the nature of breast cancer, how we know it, and how we treat it. The chapter outlines the investigation, highlighting the major questions that are raised along the way.

Taken together, chapters 5-8 (The Eyes of the World on Bisie) provide an example of how the themes discussed in chapters 2-4 ("Mining Worlds") played out in everyday life at a famously large and active site of movement: the rainforest mining town known as Bisie. For the so-called international community, Bisie became iconic of “blood minerals” in Congo, and was the focus of a couple of documentaries, including a Vice episode, a movie called Blood in the Mobile, and parts of a book on “modern slavery.” But for many Eastern Congolese, Bisie was a central site of recuperation after years of war, and also proved that the actions of ordinary, dispossessed Congolese could transform Congo into the center of the world, such that the world appeared in their midst. These four chapters on Bisie are relatively short, intended to be read as a single narrative, or short book within the book, depicting the themes of movement and enclosure in action mode, while also modeling the metaphor of the “wormhole” as a materialization of movement. Chapter 5 describes "movement" at Bisie as the author witnessed it in 2009.