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clean up

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Pablo Antonio Lillo Cea 2026-05-08 10:17:09 +02:00
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src/municipalities/02-CA.R
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@ -2,26 +2,25 @@
# 02-CA.R · Correspondence Analysis of the 2022 municipal cross-section # 02-CA.R · Correspondence Analysis of the 2022 municipal cross-section
# ============================================================================= # =============================================================================
# #
# Bourdieusian framework:
# - Individuals (rows): 290 Swedish municipalities # - Individuals (rows): 290 Swedish municipalities
# - Active columns: population-composition counts — variables that all # - Active columns: population-composition counts — variables that all
# measure "number of residents with attribute X", # measure "number of residents with attribute X",
# sharing a common unit (persons). The active set is # sharing a common unit (persons). The active set is
# deliberately restricted to age structure, # deliberately restricted to age structure,
# educational capital (Swedish-born, by gender), # educational attainment (Swedish-born, by gender),
# employment sector, and national origin. These # employment sector, and national origin. These
# variables together define the compositional profile # variables together define the profile
# of the municipality's resident population. # of the municipality's resident population.
# - col.sup (a): educational provision counts — the research object # - col.sup (a): educational provision counts
# - col.sup (b): political vote and council counts — outcomes # - col.sup (b): political vote and council counts
# - col.sup (c): infrastructure & mobility counts — dwellings, # - col.sup (c): infrastructure & mobility counts,
# vehicles, commuter flows, agricultural enterprises, # vehicles, commuter flows, agricultural enterprises,
# livestock; genuine counts but measuring different # livestock; genuine counts but measuring different
# entities (not persons), so they cannot share a # entities (not persons), so they cannot share a
# contingency table with the active columns # contingency table with the active columns
# - Outside CA: rates, proportions, continuous measures, and # - Outside CA: rates, proportions, continuous measures, and
# count variables measuring event flows (births, # count variables measuring event flows (births,
# deaths, migration) → correlated with CA row # deaths, migration) correlated with CA row
# scores post-hoc # scores post-hoc
# #
# Why restrict active variables to person-counts? # Why restrict active variables to person-counts?