Anna Alexandrova

This article presents two related challenges to the idea that, to ensure policy evaluation is comprehensive, all costs and benefits should be aggregated into a single, equity-weighted wellbeing metric. The first is to point out how, even allowing for equity-weighting, the use of a single metric limits the extent to which we can take distributional concerns into account. The second challenge starts from the observation that in this and many other ways, aggregating diverse effects into a single metric of evaluation necessarily involves settling many moral questions that reasonable people disagree about. This raises serious questions as to what role such a method of policy evaluation can and should play in informing policy-making in liberal democracies. Ultimately, to ensure comprehensiveness of policy evaluation in a wider sense, namely, that all the diverse effects that reasonable people might think matter are kept score of, we need multiple metrics as inputs to public deliberation.

In her BBC Reith Lectures on Trust, Onora O’Neill offers a short, but biting, criticism of transparency. People think that trust and transparency go together but in reality, says O'Neill, they are deeply opposed. Transparency forces people to conceal their actual reasons for action and invent different ones for public consumption. Transparency forces deception. I work out the details of her argument and worsen her conclusion. I focus on public transparency – that is, transparency to the public over expert domains. I offer two versions of the criticism. First, the epistemic intrusion argument: The drive to transparency forces experts to explain their reasoning to non-experts. But expert reasons are, by their nature, often inaccessible to non-experts. So the demand for transparency can pressure experts to act only in those ways for which they can offer public justification. Second, the intimate reasons argument: In many cases of practical deliberation, the relevant reasons are intimate to a community and not easily explicable to those who lack a particular shared background. The demand for transparency, then, pressures community members to abandon the special understanding and sensitivity that arises from their particular experiences. Transparency, it turns out, is a form of surveillance. By forcing reasoning into the explicit and public sphere, transparency roots out corruption — but it also inhibits the full application of expert skill, sensitivity, and subtle shared understandings. The difficulty here arises from the basic fact that human knowledge vastly outstrips any individual’s capacities. We all depend on experts, which makes us vulnerable to their biases and corruption. But if we try to wholly secure our trust — if we leash groups of experts to pursuing only the goals and taking only the actions that can be justified to the non-expert public — then we will undermine their expertise. We need both trust and transparency, but they are in essential tension. This is a deep practical dilemma; it admits of no neat resolution, but only painful compromise.

Psychometrics and the representational theory of measurement are widely used in social scientific measurement. They are currently pursued largely in isolation from one another. I argue that despite their separation in practice, RTM and psychometrics are complementary approaches, because they can contribute in complementary ways to the establishment of what I argue is a crucial measurement property, namely, representational interpretability. Because RTM and psychometrics are complementary in the establishment of representational interpretability, the current separation of measurement approaches is unfounded. 1Introduction2Two Approaches to Measurement 2.1Representational theory of measurement2.2Psychometrics2.3Representational interpretability3Complementarity, Conceptually 3.1Representational theory of measurement: Conditions of representational interpretability3.2Psychometrics: Evidence of representational interpretability4Complementarity in Action 4.1What is the Rasch model?4.2Rasch and conjoint measurement5Conclusion: Critics and Fruits of Complementarity

Psychometrics is one of the main approaches to social scientific measurement. It is relied upon in drug testing, economic policymaking, recruitment, and other decision-making contexts. The first aim of this article is to introduce philosophers to key aspects of psychometrics, namely, classical test theory, item response theory, and construct validity. The second aim is to show how a debate on the nature of psychological attributes manifests in psychometrics. In this debate, realists claim that psychometric measures are indicators of independently existing qualities, while operationalists argue that a measure defines its target attribute. The third and final aim is to argue that despite its poor reputation among philosophers, operationalism is a viable approach to psychometrics.