Small sample size forced coarse occupational categories, limiting finer class analysis

Evidence

With regard to the occupational status of the subjects, the sample was divided into skilled workers, unskilled workers, white-collar workers and others; further differentiation was dispensed with, as it would have led to groupings which were too small. — Rolf Wiggershaus, The Frankfurt School, 192

Categorization

• XREF: connects to: Statistical typology methods silently bake in exhaustive, mutually exclusive category rules. — Gary Goertz, Social Science Concepts and Measurement, 1335; Boston’s retarded-class assignment disparity reflected category availability and staff preference — Michael Lipsky, Street-Level Bureaucracy: Dilemmas of…, 295; Algorithms fabricate uniformity by compositing varied content into data categories — Anna Kornbluh, Immediacy, or The Style of Too Late…, 208 (+2 more)
• yield-rescued: below the book’s yield-target cutoff, included anyway for connecting to: Statistical typology methods silently bake in exhaustive, mutually exclusive category rules. — Gary Goertz, Social Science Concepts and Measurement, 1335; Boston’s retarded-class assignment disparity reflected category availability and staff preference — Michael Lipsky, Street-Level Bureaucracy: Dilemmas of…, 295; Algorithms fabricate uniformity by compositing varied content into data categories — Anna Kornbluh, Immediacy, or The Style of Too Late…, 208 (+2 more)

Broader Connections

• Equal-percentile cutoffs produce deeply unequal measured categories #complicates (0.80) — Gary Goertz, Social Science Concepts and Measurement, 899