The context of natural resource governance is often of uncertainty and change, even more so as the effects of climate change become ever more experienced. Adaptive governance and adaptive co-management have emerged as responses to the need to cope with and adapt to new information and changing situations. The chapter reviews what is understood by these terms and approaches, and identifies key characteristics and related concepts, such as resilience and uncertainty. The centrality of knowledge for adaptive approaches is recognised, with the role of, and challenges to, community, or participatory, monitoring and use of local and traditional knowledge in co-management reviewed. Forms of social, or collective, learning are then identified, recognising that social learning may occur through experimental approaches or deliberation and that feedback from learning is essential for adaptive governance.

Chapter 2 develops the theoretical foundation for why Islamist civil wars are especially intractable. We question both essentialist and instrumentalist perspectives on Islamist armed conflicts. Instead, we develop an argument based on a bargaining perspective when explaining the intractability of Islamist conflicts, which we refer to as the strategic embeddedness of Islamist civil wars. The thrust of our argument is that Islamist civil wars are embedded in a particular strategic environment – engulfed in a transnational network of groups and actors supporting the rebels and, in parallel, entangled in a web of various intergovernmental commitments and support structures backing the government side. Such international support tends to create a high degree of uncertainty in terms of the extent and nature of support, making it harder for the parties to assess one another’s resolve and capabilities, which in turn makes these conflicts less likely to end. We explain how the transnational dimension of Islamist civil wars affects the level of uncertainty in conflicts and how it can decrease the likelihood of termination, increase the risk of recurrence, and reduce the chances of conflict resolution.

In this chapter, we examine how to quantify uncertainty about model parameters, highlighting two main approaches: frequentist and Bayesian. We start by modelling a data-generating mechanism with a parametric family, where different parameter values correspond to different models. Assuming our model family can describe the mechanism, we use data to infer plausible parameters and quantify uncertainty. In frequentist inference, we build parameter estimators and study their sampling distributions across repeated data collection. Here, parameters are fixed unknown constants, and only estimators are treated probabilistically. In Bayesian inference, parameters are latent random variables. We express uncertainty through probability, combining prior beliefs about parameter values with observed data using Bayes’ rule to obtain a posterior distribution. The posterior and the frequentist sampling distribution often play similar roles and can resemble each other in practice. Computational tools like bootstrapping and Markov chain Monte Carlo help estimate sampling and posterior distributions, respectively.

Chapter 11 synthesizes the book’s insights, emphasizing that policymaking is dynamic, interactive, and iterative. Key challenges facing contemporary governance include path dependency, uncertainty, conflicting values, learning barriers, and capacity constraints. The chapter calls for investment in policy capacity, cross-sectoral collaboration, and evidence-based decision-making, and explores abductive reasoning and practical judgment as tools for navigating complexity and ambiguity. It argues for enhancing technical analysis with political acumen and for organizational cultures that support continuous learning.

The Introduction sets the scene by outlining the lives of the book’s main protagonists, young women in Calabar, and the types of uncertainty that shape their lives. The discussion builds up an understanding of the complex and opaque social terrain that these young women must deftly navigate as they work towards a future marked by marriage. In urban Nigeria, the belief in the unseen compounds other political, economic, and physical uncertainties that shape everyday life, contributing to an understanding that nothing is ever quite as it seems. The discussion outlines how young women, far from only falling victim to the irregularities of life in Calabar, turn uncertainty into a resource that they can use to manage their reputations and realise their much hoped-for futures. As well as establishing how the book contributes to anthropological and Africanist literature on uncertainty, the Introduction also opens the debate on the time of youth in Africa by focusing on feminine livelihoods and respectability. The Introduction also provides context of fieldwork and research methodology and provides a chapter outline of the rest of the book.

Drawing together the previous chapters’ discussions of feminine respectability, the Conclusion focuses on the tensions young women experience as they attempt to reconcile personal ambition with societal expectations and as they navigate quotidian life in the city alongside the longer-term objectives of ending their single status. The Conclusion reiterates the book’s two arguments, articulating how feminine youthhood is a period shaped by contingencies, which not only render young women vulnerable but also encourage them to contribute to the uncertainties that shape urban life in contemporary Nigeria. While the previous chapters have discussed how dissimulation, illusion, and concealment shape young women’s lives, and the ambiguous attitudes young women have towards these forms of uncertainty, the Conclusion questions when the fake is categorically immoral. Doing so, young women are inserted into a broader discussion of the means of sustaining, as well as the perceived threats to, social reproduction in urban Nigeria.

Chapters 2 and 3 form the ethnographic heart of the book, exploring the economic niches that form an informal welfare system largely reserved for disabled people. Chapter 2 considers brokering at the Kinshasa-Brazzaville border, an activity viewed by some as ‘given’ by the state as a form of compensation for the lack of social welfare. Examining in detail the dynamics of community and the activities performed at the border, the chapter shows how the social values underpinning personal relationships were tested in the moral dilemmas over a common rhetoric of individualism: ‘fending-for-yourself’ rather than caring for mutually dependent relationships. A moral emphasis on the value and nature of professional relationships was shaped by the knowledge that life and work at the border might only ever be a temporary arrangement, as the most dramatic incarnations of ’crisis’ (mpiaka) drew attention to the temporal frame in which these value debates took place.

The first chapter provides an orientation in the lives of disabled people in Kinshasa through a consideration of how the interlocutors were identified and identified themselves as disabled, as handicapé – a relatively narrowly defined and recently agreed-upon category of persons. People sometimes overtly pursued this identity for the occasional advantages it could provide, but recognition as an handicapé, and enforcing associated privileges, is far from straightforward. Rather than a depoliticised knowable fact of the body, making handicapé into a recognised identity continues to be politically contested and destabilised, among others through internal rivalries among disabled people and between their organisations. The chapter thus considers the role of a wide variety of disabled peoples’ organisations, and especially the bureaucracy represented by their membership cards, as means of establishing disability status. ‘Real’ membership and leadership was ultimately uncertain and based on constant mutual evaluation. Keeping uncertainties alive allows for an expression of values on the distribution of resources, while creating a productive uncertainty around the question of membership itself.

The Introduction combines a contextual introduction to disability in Kinshasa with an outline of the research problem as the tension between exceptionality and normality in a city that has long defined itself as in ‘crisis’. The interlocutors, their city, the times in which they lived, and their livelihood activities were all subject to ambiguous judgements as to whether they stood out as a negative or positive example, or if they were better viewed as simply part of the general experience of life in the wider community. The Introduction thus outlines the focus on mobility-impaired people in the grey area between work and welfare, where ‘crisis’ (mpiaka) opens a discursive space for experimentation, critique, and evaluation. The unpredictability that marks life in Kinshasa, in this respect, leads people to constantly reckon their social and economic value projects in relation to time. The Introduction introduces how crisis confronts people with choices of realising the short-term values of ‘fending for yourself’ or the long-term values of cultivating dependent relationships.

Introduces the dynamic capabilities framework – sensing, seizing, and transforming – as a strategic tool for university leaders. Explains how dynamic capabilities help institutions respond to uncertainty and change, enabling them to identify opportunities, execute initiatives, and transform operations.

This chapter demonstrates the value of re-running models under different conditions, first in sensitivity analysis to investigate the contribution of different parameters to model uncertainty, and then in Monte Carlo analysis to determine how models can be used quantitatively even in the face of uncertainty in their parameters. We use examples of risk assessment in the pre-Monte Carlo world to motivate the latter. Here we return to the mosquito control model for sensitivity analysis and look at a classic paper on cancer risk for the Monte Carlo section.

The multi-contingency model frames organizational design as a continuous executive task shaped by globalization, digitalization, AI, sustainability, and shifting societal expectations. It identifies nine interdependent components – goals and scope, strategy, environment, configuration, leadership, climate, task design and agents, coordination and control, and incentives and people – whose alignment drives performance. Extending traditional contingency theory, it integrates insights from economics, information processing, and organizational theory, viewing organizations as systems that manage complexity by balancing information-processing demand and capacity. This can mean reducing demand (e.g., modularization, predictive tools) or increasing capacity (e.g., AI, lateral communication, skilled talent). Examples from Microsoft, Aarhus University, Danish healthcare, Uber, and luxury fashion brands show how design adapts to digital innovation, sustainability, and agility. A seven-step method supports the model: getting started, strategic positioning, structuring, defining agents and leadership dynamics, setting coordination and incentives, finalizing architecture, and implementing change.

A tort is a special kind of wrongdoing. ‘Tort’ is a legal term that describes a particular category of interpersonal wrongdoing dealt with by the civil justice system. The law of torts covers a wide range of different types of misconduct, including many torts with well-known names like ‘assault’, ‘battery’, ‘trespass to land’, ‘defamation’ and ‘negligence’. The task of defining the word ‘tort’ is notoriously difficult, given that more than 70 torts are known to the common law world, each with a different focus and a distinctive set of elements to protect different personal interests.

Curiously, there does not appear to be any shared identifying characteristic nor any unified set of interests that the law of torts seeks to protect to the exclusion of any other area of the law. The search for a clear definition is further complicated by the constant state of development of the law of torts. Some torts are outdated and no longer recognised in Australia, while others that have existed in other common law jurisdictions for many years have not yet been widely accepted here.

A simple decision model that introduces the 10 ingredients of good decisions, the grammar of decision making, and a five-step framework for creating decision models.

This chapter begins by describing the consequences of uncertainty about the univariate characteristics of the data for multiple regression analysis. Next, we describe the bounds approach to inference, a general inferential framework for dealing with uncertainty when the exact limiting distribution associated with a test statistic is unknown or difficult to determine. We then introduce a bounds approach to inference that is appropriate when there is uncertainty about the properties of both the outcome and (at least some) explanatory variables. This approach uses critical value bounds to evaluate the null hypothesis of no long-run relationship based on the long-run multiplier (LRM) for each independent variable in either the ADL, GECM, or restricted versions of these models. We also describe the ARDL bounds approach to inference developed by Pesaran, Shin, and Smith, which assumes that the outcome is known to contain a unit root but allows uncertainty about the properties of the explanatory variables. We compare the relative advantages of these frameworks and provide a practical guide to critical bounds approaches to inference with two illustrative examples.