At the next Perspectives on Science seminar on Monday 28.3., Alessandra Basso (University of Helsinki) will give a presentation titled “Concepts of inequality and their measurement”. The seminar takes place in Zoom from 14:15 to 15:45.
Perspectives on Science is a weekly research seminar which brings together experts from science studies and philosophy of science. It is organized by TINT – Centre for Philosophy of Social Science at the University of Helsinki. More information about the seminar here.
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Inequality is a thick concept, because it is not simply descriptive, but implies a moral evaluation too (1). Scientists and policymakers use the term ‘inequality’ to describe the empirical distribution of a certain resource across a population. But the concept also suggests a departure from some sort of desirable equity, and therefore calls for a moral judgment about which equality is socially desirable. For instance, an influential handbook about Development Economics defines inequality as “the fundamental disparity that permits one individual certain material choices, while denying another individual those very same choices” (2). Multiple factors contribute to permit or deny these choices. This definition, therefore, reflects a broad conception of inequality, which includes multiple dimensions (income, wealth, education, freedom, etc.) and encompasses both inequality in opportunities and inequality in outcomes. When it comes to producing empirical knowledge about inequality, however, the concept of inequality is redefined as a technical term, which is narrower and deprived of its evaluative content. For measurement purposes, income inequality is defined as “a property of a variable’s frequency distribution within a population” (3). National statistical agencies, for instance, measure income inequality among households with Gini coefficients, and this measurement, in turn, depends on precise definitions of income and household, and requires choosing weighting systems and statistical tools.
The reliance on narrow, technical terms raises concerns about the significance and the reliability of the empirical knowledge produced on the bases of these concepts. How relevant are these measurements for the broader, thick concepts implementers are interested in? In contemporary scientific literature, there is increasing awareness that inequality is multidimensional and morally-charged, and scientists have developed strategies to address this issue. Some works developed the idea that inequalities about other aspects of people’s well-being (like health, nutrition, education, and political freedoms) should be measured too (4). Others, instead, bring in a subjective conception of inequality, and measure people’s perceptions about inequality and their demand for redistribution (5). My paper discusses the potentials and limitations of these strategies. Both strategies have the potential to enrich the empirical knowledge based on narrow, technical terms and can provide a broader view. However, I argue that they face challenges that pull in opposite directions, and therefore are hardly compatible.
The measurement of multiple dimensions of social inequality faces the problem that no measurement can take into account all aspects of inequality at the same time (and scientists disagree about which aspects should be taken into account and why). If the concept of inequality is too broad, it may be unsuitable for use in science and policy. In subjective measurements of inequality, instead, it is difficult to trace the different factors that contribute to people’s perceptions and concerns, and this brings about issues of conceptual clarity. It is difficult to intervene directly on people’s perceptions in order to disentangle different factors, and the effects of interventions are hardly traceable (6). Subjective conceptions of inequality, therefore, tend to be much broader than objective concepts, even when these are enriched with multiple dimensions.
(1) Anderson, E. (2002). Situated knowledge and the interplay of value judgments and evidence in scientific inquiry. In In the scope of logic, methodology and philosophy of science (pp. 497–517). Springer.
(2) Ray (1998).Development Economics. Princeton: Princeton University Press.
(3) McGregor, Thomas, Brock Smith, and Samuel Wills. 2019. “Measuring Inequality.” Oxford Review of Economic Policy 35 (3): 368–95.
(4) Chancel, L., Piketty, T., Saez, E., Zucman, G. et al. World Inequality Report 2022, World Inequality Lab.
(5) Ciani, Fréget, Manfredi (2022) Learning about inequality and demand for redistribution: A meta-analysis of in-survey informational experiments, OECD papers on Well-being and inequalities No. 02.
(6) Eronen, M. I. and Bringmann, L. F. (2021). The theory crisis in psychology: How to move forward. Perspectives on Psychological Science 16(4), 779-788.
Alessandra Basso is a PhD candidate at the University of Helsinki’s TINT centre for the Philosophy of Social Science. In 2022, she will join the Department of History and Philosophy of science at the University of Cambridge as a Newton International Fellow, funded by The British Academy. She received an MA in Philosophy from the University of Bologna and an MSc in Philosophy of the Social Science from the London School of Economics. Her doctoral dissertation concerns the epistemology of measurement in the social sciences, in psychology and psychiatry; it explores measurement practices in these fields and the specific challenges they face. Her current research focuses on the conceptual and methodological foundations of inequality measurement. Her articles have appeared in European Journal of Philosophy of Science, Studies in History and Philosophy of Science, and The British Journal for Philosophy of Science.