{"id":"W2013108856","doi":"10.1177/0049124105280198","title":"Mapping Social Distance","year":2005,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Multidimensional scaling; Ethnic group; Census; Metropolitan area; Immigration; Diversity (politics); Geography; Social distance; Sociology; Social group; Racial diversity; Census tract; Cultural diversity; Geographical distance; Economic geography; Regional science; Demography; Demographic economics; Social science; Statistics; Mathematics; Anthropology; Population","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01516615,0.000123683,0.0003043035,0.0001046569,0.003825143,0.0001062391,0.0004966609,0.0003161837,0.001070685],"category_scores_gemma":[0.004798304,0.00009757034,0.0001534272,0.0007867138,0.002292949,0.0001520047,0.0001967372,0.0008211015,0.0002499913],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003292255,"about_ca_system_score_gemma":0.0001617861,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001955951,"about_ca_topic_score_gemma":0.0001139387,"domain_scores_codex":[0.9901086,0.007365673,0.0002833762,0.0004165351,0.0008622871,0.0009635195],"domain_scores_gemma":[0.9945496,0.004638709,0.00006248639,0.0001449977,0.0004356699,0.0001684943],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002883735,0.0001233424,0.006856205,0.00001076548,0.00005093964,0.000004607016,0.1086555,0.0000012311,0.0005464053,0.4363887,0.01783628,0.4294972],"study_design_scores_gemma":[0.000179424,0.00003837603,0.01379799,0.000005858285,0.000002894538,1.814187e-7,0.04835332,0.00004901724,0.00004713657,0.09474343,0.8426151,0.0001672858],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.07082711,0.005578351,0.1221271,0.09367476,0.0005747584,0.001006778,0.00001754669,0.0005672908,0.7056262],"genre_scores_gemma":[0.8924284,0.0007689943,0.08873352,0.0005881703,0.003458929,0.0001285231,0.000003075835,0.00001414405,0.01387625],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8247788,"threshold_uncertainty_score":0.9998425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.496170104316695,"score_gpt":0.6084512661669489,"score_spread":0.1122811618502539,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}