This chapter shows how human obedience is captured in an experimental setup, and how such research methodology can help us understand how people can comply with orders to hurt another person on a neurological level. By reviewing past experimental research, such as the rat decapitation study of Landis, the studies of Stanley Milgram on destructive obedience, and the Utrecht studies on obedience to non-ethical requests, this chapter shows that under certain circumstances, a majority of individuals could be coerced into inflicting physical or psychological harm on others at levels generally deemed unacceptable, even without any tangible social pressures such as military court or job loss. The chapter also describes a novel method where people can administer real painful electric shocks to someone else in exchange for a small monetary reward, and describes how such a method allows neuroscience investigations that would focus on the neural mechanisms associated with obedience.

Over the years, the Serengeti has been a model ecosystem for answering basic ecological questions about the distribution and abundance of organisms, populations, and species, and about how different species interact with each other and with their environment. Tony Sinclair and many other researchers have addressed some of these questions, and continue to work on understanding important biotic and abiotic linkages that influence ecosystem functioning. In common with all types of scientific inquiry, ecologists use predictions to test hypotheses about ecological processes; this approach is highlighted by Sinclair’s research that explored why buffalo and wildebeest populations were rapidly expanding. Like other scientists, ecologists use observation, modeling, and experimentation to generate and test hypotheses. However, in contrast with much biological inquiry, ecologists ask questions that link numerous levels of the biological hierarchy, from molecular to global ecology.

In working with network data, data acquisition is often the most basic yet the most important and challenging step. The availability of data and norms around data vary drastically across different areas and types of research. A team of biologists may spend more than a decade running assays to gather a cells interactome; another team of biologists may only analyze publicly available data. A social scientist may spend years conducting surveys of underrepresented groups. A computational social scientist may examine the entire network of Facebook. An economist may comb through large financial documents to gather tables of data on stakes in corporate holdings. In this chapter, we move one step along the network study life-cycle. Key to data gathering is good record-keeping and data provenance. Good data gathering sets us up for future success—otherwise, garbage in, garbage out—making it critical to ensure the best quality and most appropriate data is used to power your investigation.

The image of Darwin as a lone thinker, a theoretician who worked largely in isolation rather than a hands-on scientist, has no single origin but is stubbornly persistent. Modern accounts that do feature him as a practical researcher tend to emphasize the domestic setting of his work, focusing on experiments that can be replicated in a modern house, garden, or school. But contemporary evidence, in particular from Darwin’s extensive correspondence, demonstrates that he was an ingenious and innovative experimenter, keenly aware of advances in science, and often at the cutting edge both in the nature of his investigations and in the technologies he employed. Far from working alone on gathering facts and grinding out his theories, Darwin was expert at cultivating and exploiting contacts. He actively sought collaboration with all sorts of people around the world, both asking for their help and encouraging their own investigations. Although he rarely travelled after settling in the village of Down in Kent as a young married man, Darwin’s version of ‘working from home’ was far from solitary: he was surrounded not only by a large and happy family but by governesses, gardeners, friends, neighbors, and visitors, who acted as critics, assistants, editors, and even as research subjects.

Featuring an explanation of Enlightenment thought on agronomy and political economy, Chapter 3 examines the efforts to make Mauritius a self-sufficient island through the importation and naturalisation of plants (primarily foodstuffs and fodder, also some industrial materials, and a few ornamental plants). It explores how newly introduced and ‘old’ plants were cultivated and how local knowledge, which was gathered together with the plants in their countries of origin, was implemented. It highlights the practical significance of knowledge about plants in relation to their cultivation of Malagasy and non-European communities across Asia. It seeks to understand how settlers sought to cultivate foreign, newly introduced staple crops, such as rice, root vegetables, and fruit trees. Stressing the importance of non-European knowledge, the chapter looks at the interplay of this knowledge between its practical implementation and environmental factors. The chapter reveals that cultivation techniques were difficult to implement and often led to a crop’s failure.

This chapter follows the definition of ‘empirical legal studies’ as research which applies quantitative methods to questions about the relationship between law and society, in particular with the aim of drawing conclusions about causal connections between variables. Comparative law does not typically phrase its research as being interested in questions of causal inference. Yet, implicitly, it is very much interested in such topics as it explores, for example, the determinants of legal differences between countries or when it evaluates how far it may be said that one of the legal solutions is preferable. It is thus valuable that significant progress has been made in empirical approaches to comparative law that may be able to show robust causal links about the relationship between law and society. This chapter outlines the main types of such studies: experiments, cross-sectional studies, panel data analysis and quasi-experiments. However, it also shows that such studies face a number of methodological problems. This chapter concludes that often it may be most promising to combine different methods in order to reach a valid empirical result.

I create and test three interventions that are meant to dampen negative partisanship without diminishing positive partisanship: the impact of cross-cutting identities, unifying identities, and the role of party leaders.

At a time in U.S. politics when advocacy groups are increasingly relying on supporters to help advance their agendas, this chapter considers how intersectional advocates are mobilizing their supporters in Chapter 6. While membership in women’s advocacy organizations has decreased over the years, supporters that volunteer their time to advocacy organizations to advance their policy goals has been largely overlooked. Yet, these supporters are important contributors to intersectional advocacy. In Chapter 6, two original survey experiments are presented with the supporters from this organization that also engages in intersectional advocacy. Each experiment contain authentic policy platforms that either present an intersectional advocacy approach or a traditional single issue policy approach to supporters. The findings from these experiments answer the final question: does intersectional advocacy resonate with the intersectionally marginalized populations it aims to serve, and if so, to what extent does it mobilize them to participate in the policymaking process? This chapter highlights the role of supporters in advancing these policy efforts while showcasing tangible

Chapter 5 moves from theory into evidence and discusses how empirical economists think about causality. First, the chapter covers common issues that make it difficult to have confidence in causal claims based on associational evidence alone. Then, experimental evidence is discussed: how to run an experiment, common pitfalls that can undermine confidence in experimental evidence, and what can be done to avoid them. Next, major experimental studies on the impact of health insurance are described. Finally, the chapter discusses the concept of quasi-experimental evidence and how it fits into economics. The end of chapter supplement discusses ethics in research with human subjects and the role of institutional review boards.

This chapter deals with research priorities that were obtained during the writing of this book. We first illustrate the recent insights that were published since the publication of the first volume. New research topics deal with further exploring and identifying critical habitat components and the effect of land improvement initiatives. Demographics need to be studied in less covered areas using methods that have been perfectioned in the typical highly researched countries. Examining responses of Little Owl populations to land uses and the effects of abiotic environmental factors should allow for more quantitative management and follow-up on the effectiveness of taken measures. The adoption of the information-theoretic approach, focus on process variation and searching for mechanisms will need more statistical background and thoroughness, leading to even more long-term observational studies and focus on the cumulative effects. To do this in an optimal way, more experiments are urgently needed, to enable controling for certain parameters. Finally there is a need for the expansion of the investigated geographic range and an increase in research and experiment maturity in emerging countries, hopefully enabled by highly mature research teams and international co-operation.

Surveys in trademark, trade dress, and false advertising cases often focus on liability. For example, in trademark cases, the focus of survey evidence has often been on whether consumers confuse the two marks. Similarly, survey evidence in false advertising cases has focused on whether the at-issue advertising claim misleads or deceives consumers. Surveys that address these issues of alleged confusion or deception measure consumer “perception,” and the results are often the centerpiece of a plaintiff’s liability arguments. While such questions may be central to cases that seek an injunction or aim to prevent the issuance of a new trademark, they are less relevant in questions of impact or injury.