Adults undertaking the endeavor of learning a new language can attest to the difficulty involved with producing the sounds and prosody of the target language. A principal aim of research on adult speech production is to comprehend the mechanisms and processes that differentiate adult bilingual speech development from bilingual speech that develops earlier in life. It is clear that individuals who learn an additional language in adulthood typically encounter some difficulties that early learners do not. In particular, these difficulties arise at the segmental level when acquiring novel sound categories and novel sound contrasts, as well as at the suprasegmental level when learning to produce non-native prosodic structures related to intonation, stress, rhythm, tone, and tempo. The present chapter provides a selective overview of the current state-of-the-art in adult bilingual speech production. Furthermore, this chapter considers theoretical and methodological areas for improvement, as well as avenues for future research.

Scientific disciplines are characterized by cultures of practice that shape how research is conducted. The conventional research designs of studies by human behavioral ecologists entail both pros and cons. This chapter considers alternatives that would allow human behavioral ecologists to marshal the empirical evidence that is needed for convincing answers to long-standing debates. In particular, the chapter advocates for greater emphasis on long-term, individual-based field research. Data acquired via prospective panel studies can be used to examine the dynamic processes that unfold over long periods of time, including life span and intergenerational processes. Remedies are needed to the structural obstacles that limit the implementation of prospective panel studies, including logistical and funding constraints. The chapter also addresses the disadvantageous academic research culture that incentivizes scientists to pursue status and prestige instead of research objectives with greater long-term value. Methods to support longitudinal research are discussed, including approaches to data management and data analysis. The chapter concludes by highlighting opportunities for rising generations of human behavioral ecologists to reshape the culture of research practice in order to advance principled, ethical, and compelling approaches to the comparative study of human behavior.

Chapter 1 provides philosophical foundations for the arguments of this book in discussing the issue of scientific objectivity in economics. It criticizes a closed science, “view from nowhere” conception of economics, and defends an open science, “view from somewhere” conception of economics as an objective science. The first conception is ascribed to current mainstream economics, is associated with its principle practices – reductionist modeling, formalization, limited interdisciplinarity, and value neutrality – and has as its foundation the abstract Homo economicus conception. Two problematic consequences of these practices are value blindness regarding the range and complexity of human values; fatalism regarding human behavior in employing a tenseless rather than tensed representation of time. In contrast, the principle practices of an open science, “view from somewhere” conception of economics as a science – complexity modeling, mixed methods, strong relationships to other disciplines, and value diversity – provide the foundations of a socially and historically embedded individual conception. The chapter closes with discussion of the question: Might mainstream economics be a science bubble?

In the concluding chapter, the author investigates whether it is possible to move beyond the inevitability of metrics, and what doing so might imply. The author shows that the greatest challenge lies in individualized thinking about science and the focus on the accumulation of economically conceived value by institutions. This is because the problem does not lie in metrics. Rather, the problem is an underlying logic of economization, and it is only by uprooting it that one could change today’s academia. Still, any new logic would also be legitimized by new metrics. Therefore, this book’s conclusion is neither a proposal for a ‘responsible use of metrics,’ nor a call to abandon the use of all metrics in academia. A third way is needed. Thus the book’s key contribution is its call for a rejection of these two potential responses and its insistence on the necessity that we set out now on a course that can offer hope of charting such a third response. In this spirit, the author sketch out seven principles that should be kept in mind when rebuilding not only a new system of scholarly communication but, more importantly, an academia that is not driven by metrics.

Traditionally, primate cognition research has been conducted by independent teams on small populations of a few species. Such limited variation and small sample sizes pose problems that prevent us from reconstructing the evolutionary history of primate cognition. In this chapter, we discuss how large-scale collaboration, a research model successfully implemented in other fields, makes it possible to obtain the large and diverse datasets needed to conduct robust comparative analysis of primate cognitive abilities. We discuss the advantages and challenges of large-scale collaborations and argue for the need for more open science practices in the field. We describe these collaborative projects in psychology and primatology and introduce ManyPrimates as the first, successful collaboration that has established an infrastructure for large-scale, inclusive research in primate cognition. Considering examples of large-scale collaborations both in primatology and psychology, we conclude that this type of research model is feasible and has the potential to address otherwise unattainable questions in primate cognition.

Part of what distinguishes science from other ways of knowing is that scientists show their work. Yet when probed, it turns out that much of the process of research is hidden away: in personal files, in undocumented conversations, in point-and-click menus, and so on. In recent years, a movement toward more open science has arisen in psychology. Open science practices capture a broad swath of activities designed to take parts of the research process that were previously known only to a research team and make them more broadly accessible (e.g., open data, open analysis code, pre-registration, open research materials). Such practices increase the value of research by increasing transparency, which may in turn facilitate higher research quality. Plus, open science practices are now required at many journals. This chapter will introduce open science practices and provide plentiful resources for researchers seeking to integrate these practices into their workflow.

Chapter 1 discusses of the evolution of experiments, illustrating this development through the field of political science. The author argues that the discipline currently finds itself in a new era, parts of which apply to all of the social sciences. This new era began around 2010 and reflects the confluence of experiments achieving widespread acceptance in the discipline, technological advances, and the open science movement (these latter two dynamics have affected all of the social sciences). The era introduces many opportunities but also novel challenges. Ironically, the ease of conducting experiments today has the potential to undermine their quality. I conclude the chapter by discussing the motivation for the primer and reviewing the remainder of the book.

Chapter 5 delves into the steps that occur prior to, during, and after an experiment – including arriving at questions to explore with an experiment; documenting the steps in the process of conducting an experiment; and considering whether to replicate one’s findings after an experiment. This discussion touches on the themes of the aforementioned open science movement, offering in many instances a cautionary perspective.

The National Institutes of Health (NIH) is the largest funder of Alzheimer’s disease and related demententias (AD/ADRD) research in the world. The National Institute on Aging (NIA), part of the NIH, leads the federal effort on AD/ADRD research. Since 2005 the NIA has been developing a robust translational research program for the treatment and prevention of AD dementia. In 2011, the National Alzheimer’s Project Act became law and ordered the creation of a National Plan to Address Alzheimer’s Disease. The National Plan was first released in 2012 and the first goal of the plan is to find effective ways to treat or prevent dementia by 2025. Since the first the release of the first National Plan in 2012, NIA’s funding for AD/ADRD research has steadily increased, allowing continued expansion and diversification of the drug development portfolio and the development of translational infrastructure programs to accelerate the discovery of effective therapies.