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Pablo Antonio Lillo Cea 2026-05-08 10:17:09 +02:00
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# 02-CA.R · Correspondence Analysis of the 2022 municipal cross-section
# =============================================================================
#
# Bourdieusian framework:
# - Individuals (rows): 290 Swedish municipalities
# - Active columns: population-composition counts — variables that all
# measure "number of residents with attribute X",
# sharing a common unit (persons). The active set is
# deliberately restricted to age structure,
# educational capital (Swedish-born, by gender),
# educational attainment (Swedish-born, by gender),
# employment sector, and national origin. These
# variables together define the compositional profile
# variables together define the profile
# of the municipality's resident population.
# - col.sup (a): educational provision counts — the research object
# - col.sup (b): political vote and council counts — outcomes
# - col.sup (c): infrastructure & mobility counts — dwellings,
# - col.sup (a): educational provision counts
# - col.sup (b): political vote and council counts
# - col.sup (c): infrastructure & mobility counts,
# vehicles, commuter flows, agricultural enterprises,
# livestock; genuine counts but measuring different
# entities (not persons), so they cannot share a
# contingency table with the active columns
# - Outside CA: rates, proportions, continuous measures, and
# count variables measuring event flows (births,
# deaths, migration) correlated with CA row
# deaths, migration) correlated with CA row
# scores post-hoc
#
# Why restrict active variables to person-counts?