Write regularly and pay attention to your personal writing processes. When it’s writing time, it’s writing time. Save the self-editing for later. Choose a self-editing strategy that targets the kinds of writing problems you know you usually have: surface, sentence, paragraph, or global level. Don’t be afraid to change strategies or try multiple strategies; taking more looks at your paper is always better. Peer review as it’s practiced in political science is about reviewing research design and execution, not line editing. For all papers, look for theory grounded in concepts, hypotheses that are directly observable implications of the theory, and measurement that is valid in the context of the research. For qualitative research, consider case selection, measurement, and whether the conclusions are commensurate with the scope of the theory and tests. For quantitative research, consider issues of measurement and case selection, and be alert for specification errors and analytical pitfalls the author might have missed. Helpful peer reviews provide concrete guidance about weaknesses in the paper and often include specific suggestions or requests for additional development of the paper.

This chapter looks specifically at neural circuits, assemblies of neurons that influence sensory, motor and cognitive functions. I discuss the conventional criteria for understanding these circuits, which are reductionist in their approach, and highlight various caveats in experimental and conceptual approaches that are routinely followed. I also consider the use of motifs, arrangements of component parts of a circuit that serve specific functions like electronic components. I follow others in highlighting the utility of appealing to motifs, but again highlight caveats of these motifs that mean we cannot assume their presence or the function when we know they are present. I finish by discussing aspects that have been identified over the last few decades that may add to the aspects we need to study, including plasticity, glial cells, variability and ephaptic signals.

This chapter considers reductionism, a major aspect of neuroscience research. I consider reductionist claims that we can only understand nervous systems from knowledge of their component parts. I then consider reductionist approaches and what we have learnt by following them, highlighting that a complete reductionist account of any nervous system region hasn’t been and is probably impossible to achieve. I then discuss decomposable hierarchical and non-decomposable heterarchical systems, and how relational aspects suggest we cannot understand the latter systems from cataloguing their individual components. I then discuss two effects that have received little attention despite being known for decades – volume transmission and ephaptic signalling – that highlight the need to consider component parts in relation to the whole system. I finish by discussing non-reductionist views, equipotentiality, cybernetics, the holonomic brain and embodied cognition, highlighting, as many have in the past, that debating between reductionist and non-reductionist approaches is a false dichotomy.

This chapter looks at social influences on neuroscience. It outlines that science is a social system, and subject to various social pressures that can affect what we study, how we study it, and how we interpret the data we obtain. This includes financial conflicts of interest, claims to priority, scientific prizes, peer review, ‘scientmanship’ that attempts to promote or suppress certain scientific views and scientists, and the recent quantification of social pressures in science from surveys that suggest that social pressures and career structures introduce behaviours that make science a difficult career for those lower in the scientific hierarchy, including racial and sexual biases, and can see those higher up using their prominence to affect how science is done and the claims made. I highlight that awareness of these negative social influences is starting to lead to approaches that aim to address these issues.

This chapter focuses on aspects of the philosophy of science, in particular the twentieth century views of Karl Popper and Thomas Kuhn. It briefly covers earlier aspects, including Francis Bacon and William Whewell who highlighted the need for, and influence of, subjective factors in science. In discussing Popper, it considers inductive and deductive reasoning and his falsification approach, while discussion of Kuhn focuses on his view of scientific paradigms, normal science, anomalies and crises, and paradigm shifts and scientific revolutions. It highlights both Popper’s and Kuhn’s views using neuroscience examples, including chemical synaptic transmission, animal electricity and adult neurogenesis. The conclusion is that there is no formal scientific method, no formula for discovery: scientists use, and need to use, a diversity of approaches.

Both qualitative and quantitative methods provide rigorous ways to establish and assess causality, though their understandings of causality and techniques for doing so differ. Qualitative and quantitative techniques are generally complementary rather than substitutes or opposites. Common quantitative tools include cross-tabulation, regression, and logit/probit models; which is appropriate typically depends on the level of measurement of the dependent variable. Common qualitative tools include two within-case techniques, process tracing and analytic narratives, and three between-case techniques, case control, structured focused comparison, and content analysis. “Intermediate-N” techniques exist for research questions whose number of cases is greater than that typically used for qualitative analysis but below the threshold for successful quantitative analysis, along with Big Data approaches for extreme-N analysis, content analysis techniques for corpora, and mixed methods approaches.

A framing case study examines a debt dispute between a Wall Street investor and Argentina that resulted in the seizure of an Argentine warship in Ghana. Then the chapter tackles the topic of upholding international law. The chapter discusses: (1) international legal enforcement, including major bodies, when these bodies refuse to rule, and access to non-state actors; (2) domestic legal enforcement, including jurisdiction and various forms of immunity; and (3) political enforcement via coercion and persuasion.

This chapter explores how to get and prepare quantitative data prior to analysis. Use theory to identify the unit of analysis for your study, then determine the population and sample for your study. Be sure to capture appropriate variation in the DV and be alert for selection bias in how cases enter the sample. Issues of validity and reliability can potentially cause major problems with your analysis. Again, use your theory to carefully match indicators to concepts to minimize the risk of these problems. Think through the data collection process and plan ahead to maximize efficiency; gather all data for control variables and robustness checks in a single sweep, if possible. Much data, particularly for standard indicators of common concepts, is freely available online through a variety of sources, and your library probably also subscribes to other quantitative databases. Collecting new data is substantially more time-consuming than using previously-gathered data, but it is often necessary to test novel theories. Whether you use existing data or novel data, be sure to define your data needs list before beginning data collection, allow sufficient time, and document and back up everything.

This chapter considers induction, deduction and abduction as methods of obtaining scientific knowledge. The introductory section again ends by highlighting that there is no single method, and refers to claims that scientific reasoning uses various heuristics or rules of thumb based on the specific approach and the background information we have, and that we should recognise that this can introduce various errors of reasoning: by being aware of the potential for making these errors, we are better able to guard against making them. The bulk of the chapter then looks at specific logical fallacies, using neuroscience examples to illustrate them. These include ad hoc reasoning; begging the question; confusing correlation for causation; confirmation and disconfirmation biases; false dichotomies; false metaphors; the appeal to authority, tradition and emotion; the mereological fallacy; the naturalistic fallacy; and straw man arguments.

A framing case study discusses European Union trade rules that ban the sale of all products made from seals. Then the chapter provides an overview of international trade law. The chapter discusses: (1) how states have historically promoted international law, including major concepts and the evolution of trade institutions; (2) major obligations under contemporary trade law, including rules for market access and treatment standards; and (3) major exceptions under trade law that allow states to restrict trade to prevent unfair trade, safeguard economies from unexpected shocks, protect competing values (like human health and the environment), and preserve national security.

A framing case study examines South Africa’s allegation in early 2024 that Israel committed genocide in Gaza. Then the chapter examines: (1) the history of international law, from ancient societies through the Middle Ages and the classical, positivist, and modern eras; (2) important actors in international law, including states, international organizations, peoples (groups), individuals, and non-governmental groups; and (3) the critical, contractual, and sociological perspectives on how international law can influence politics.