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Measuring Descriptive Representation
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AI
DOI：10.1080/00344893.2026.2663825.png)
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Abstract
En 中文
Studies of descriptive representation typically use a percentage 'gap' or 'ratio' to measure under- or over-representation. I discuss this approach and its limitations before proposing an alternative: using measures of disproportionality to measure multigroup representation relative to population benchmarks. I then extend the approach to show how representation along one dimension of identity can be compared across demographic subgroups. I apply these measures to the representation of occupational class in the Australian Parliament (1986-2023) and then expand the analysis to show that women are more likely to represent typically female professions than men are to represent typically male professions. Disproportionality avoids problems with existing measures such as category concatenation, which can mask severe distortions in subgroup representation, and complications in operationalising concepts such as class. The approach supports comparative cross-national study across several areas of descriptive representation from race and ethnicity, to social class, gender, age, religion, or geography.
Keywords:
Descriptive representation
class
race
gender
disproportionality
Australia