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This chapter highlights two conceptual roadblocks to systematic comparisons of competing ecological communities and crime models. First, key indicators in several communities and crime models are plagued by semantic ambiguity. In essence, different researchers connect the same indicators to different constructs. Second, researchers rarely engage in systematic, multimethod ecological construct validation to clarify which indicators clearly belong to which constructs. Multimethod patterns of convergent and discriminant validation are rarely examined. Of course, such examinations are particularly challenging when examining spatially aggregated indicators. The establishment of discriminant validity, a key part of the construct validation process, is needed but challenging to accomplish with data aggregated by geographic proximity. The solution is to first adopt a unified perspective on the construct validation process, which opens up the range of empirical relationships relevant to establishing construct validity. The second is to carry out the unified construct validation activities using a Boudon/Coleman boat metamodel aligned with methodological individualism.

This chapter deals with construct-related evidence for the validity of test scores. Evaluating construct-related evidence for validity involves evaluating the logical arguments and empirical evidence supporting the central claim (implied or explicit) in assessment—that the scores from an assessment can be interpreted and used in a particular way. Score interpretations may include predictions about examinees' most likely performance on a criterion (e.g. piloting an airplane or success in college) or to make inferences about examinees' measures on internal constructs (e.g. depression, reading comprehension, attitudes toward science). Evidence is needed to determine whether these inferences can be made.

This chapter focuses on the types of research needed to support (or refute) interpretations and uses of test scores. It begins by discussing studies to investigate whether there is support for score interpretations. It then presents examples of research for investigating score uses. Finally, it considers the social consequences of test score interpretations and uses.

Among the scientists and policymakers, measurability of well-being is now almost uncontroversial—only the individual measures are. Philosopher Daniel Hausman, however, argues that well-being in the proper sense is too person-relative and hence heterogeneous. It is not a quantity that can be measured on the population level. This chapter agrees that there is a sense of well-being—the all-things-considered individual well-being—on which it is likely not measurable but disagrees that therefore well-being is not measurable in any sense. Crucial to measurement is the existence of generalisations between core components of well-being and observable indicators. Such generalisations are available if well-being is predicated of kinds of people, rather than of individual lives. Assuming this focus on well-being of kinds, validity of most existing measures of well-being is secured by the process of construct validation, whose logic relies on a plausible ideal of balancing all evidence.

This chapter begins by discussing criminological scholars' concerns about the lack of integration across levels of theorizing, i.e. the failure of criminological theory to understand the connections between macrosocial, microsocial, and individual factors. It then sets out the book's main purpose, which is to describe four issues which, because they have been overlooked, have blocked theoretical integration in community criminology. It links these issues to key matters outside of criminology and provides an integrated framework for considering the four concerns. These four issues are: spatial scaling, temporal scaling, construct validation, and selection effects. The remainder of chapter provides definitions of terms used in the study, an introduction to the Boudon-Coleman “boat” metamodel, and an overview of the subsequent chapters.