The philosophy of measurement studies the conceptual, ontological, epistemic, and technological conditions that make measurement possible and reliable. A new wave of philosophical scholarship has emerged in the last decade that emphasizes the material and historical dimensions of measurement and the relationships between measurement and theoretical modeling. This essay surveys these developments and contrasts them with earlier work on the semantics of quantity terms and the representational character of measurement. The conclusions highlight four characteristics of the emerging research program in philosophy of measurement: it is epistemological, coherentist, practice oriented, and model based.

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Old and New Problems in Philosophy of Measurement

New Methodological Perspectives on Observation and Experimentation in Science

Theory-ladenness is the view that observation cannot function in an unbiased way in the testing of theories because observational judgments are affected by the theoretical beliefs of the observer. Its more radical cousin, incommensurability, argues that because there is no theory-neutral language, paradigms, or worldviews, cannot be compared because in different paradigms the meaning of observational terms is different, even when the word used is the same. There are both philosophical and practical components to these problems. I argue, using a procedurally-defined, theory-neutral experiment that paradigms are indeed commensurable. The practical problems of theory ladenness include experimental design, failure to interpret observations correctly, possible experimenter bias, and difficulties in data acquisition. I suggest that there are methods to deal with these problems, although sometimes they cannot be dealt with completely. I believe that the philosophical problems of theory-ladenness have been solved, although the practical problems remain.

The Theory-Ladenness of Experiment

There is an increasing demand in the field of science education for the incorporation of philosophical and sociological aspects that are related to the scientific enterprise in school curricula, to the extent that the incorporation of these aspects is now considered a necessity. Several of these aspects can be categorised within the framework of the nature of science, or NOS. We warn that a possible misinterpretation of the common view of NOS tenets can lead to epistemic relativism. We pay special attention to the empirical and objective nature of science because these important features, properly understood, can help eliminate subjective flaws and protect against relativism. Some of the epistemological concepts that are relevant to this discussion are disambiguated in an attempt to prevent the temptation to take views to an extreme, as has occurred in some cases. We expect this analysis to contribute to the extant literature by improving how science is presented in the classroom without oversimplifying scientific practice.

The 'Nature of Science' and the Perils of Epistemic Relativism.

Research findings showing the ubiquity of Pareto and ‘power-law’ distributions in the social and organisational worlds underlie increasing calls for complexity-driven ideas to be applied more frequently to organisational and management research. Power laws indicate well-formed Pareto distributions. Given that the world of business is, then, quite likely Paretian rather than Gaussian, phenomena in the long tails are often more important than worrying about the average. Consequently, how to modify strategic attention and what to tell managers? Basic ideas highlighting key differences between Gaussian and Paretian approaches are first reviewed. Then, five specific cases highlighting the managerial tails of Pareto distributions are discussed. These illustrate how overall managerial effectiveness is improved by managing the Pareto tails rather than relying on conventional wisdom to manage ‘average’ behaviour. Insights and effective strategies better tuned to Pareto-distributed managerial practice follow.

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Managing in a pareto world calls for new thinking

Can a Theory-Laden Observation Test the Theory?

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Can a Theory-Laden Observation Test the Theory?