Eleven callables operationalising Goffman's "total institution" framework (Goffman 1961) on the OTIS dataset:
Details
morie_otis_repeat_placement_concentration(b09)morie_otis_within_year_placement_count(b01)morie_otis_within_year_region_diversity(b01)morie_otis_mortification_cooccurrence(b01)morie_otis_disciplinary_medical_overlap(b01)morie_otis_embedding_distribution(b02)morie_otis_intra_year_transition_matrix(a01)morie_otis_path_complexity_gini(b01)morie_otis_region_alert_state_richness(b01)morie_otis_regC_demog_contingency(b01)morie_otis_irr_glmm_vm(b01): Poisson + NB2 IRR (requires MASS for the negative-binomial fit; falls back to Poisson-only when MASS is unavailable).
All metrics are intra-fiscal-year by construction. OTIS
UniqueIndividual_ID is anonymised as YYYY-XXXXX-AA,
randomly reassigned each fiscal year and each dataset file, so
longitudinal individual-level and cross-dataset linkage are
impossible by design (see docs/methods/otis_linkage.md).
The variable_taxonomy.R registry enforces this with
cross_year_safe = FALSE.
References
Goffman, E. (1961). Asylums: Essays on the social situation of mental patients and other inmates. Anchor Books.
Hill, B. M. (1975). A simple general approach to inference about the tail of a distribution. The Annals of Statistics, 3(5), 1163-1174.
Clauset, A., Shalizi, C. R., & Newman, M. E. J. (2009). Power-law distributions in empirical data. SIAM Review, 51(4), 661-703.