Statistical Methods and the Meaning of Probabilities. A Philosopher Looks at Statistics

The talk starts out with a short introduction to the philosophy of probability. I highlight the need to interpret probabilities in the sciences and motivate objectivist accounts of probabilities. Very roughly, according to such accounts, ascriptions of probabilities have truth-conditions that are independent of personal interests and needs. But objectivist accounts are pointless if they do not provide an objectivist epistemology, i.e., if they do not determine well-defined methods to support or falsify claims about probabilities. In the rest of the talk I examine recent philosophical proposals for an objectivist methodology. Most of them take up ideas well-known from statistics. I nevertheless find some proposals incompatible with objectivist aspirations.

Voting Power and Probability

Voting power is commonly measured using a probability. But what kind of probability is this? Is it a degree of belief or an objective chance or some other sort of probability? The aim of this paper is to answer this question. The answer depends on the use to which a measure of voting power is put. Some objectivist interpretations of probabilities are appropriate when we employ such a measure for descriptive purposes. By contrast, when voting power is used to normatively assess voting rules, the probabilities are best understood as classical probabilities, which count possibilities. This is so because, from a normative stance, voting power is most plausibly taken to concern rights and thus possibilities. The classical interpretation also underwrites the use of the Bernoulli model upon which the Penrose/Banzhaf measure is based.

The construct of career success: measurement issues and an empirical example

The aim of the present paper is twofold. We first give an overview of the multi-faceted construct of career success with its “objective” (real attainments) and “subjective” (perceived attainments) components and with the different methodologies measuring them (“subjectivist” vs. “objectivist” approaches). We also discuss the relationship between the different components of career success as revealed in the literature. Our second aim is to show that the interrelationship between the different facets of career success varies with the employment context. We analyze subjective and objective career success measures collected from professionals working either in the private sector, in the public sector, or that are self-employed. Our findings show that objective success and subjective success are more closely related in the private and self-employment sectors than in the public sector. Moreover, the interrelationship between objective and subjective success varies with the specific subjective success measure chosen. It is stronger for an “other-referent” subjective success measure than for a “self-referent” subjective success measure. Conclusions regarding the measurement of career success as well as regarding the relevance of subjective success for studying occupational careers are drawn.