{"id":"W2987728564","doi":"10.1093/geroni/igz038.1601","title":"DOES DEMENTIA POLICY ACCOUNT FOR DIVERSITY? AN ANALYSIS OF CANADIAN DEMENTIA POLICIES","year":2019,"lang":"en","type":"article","venue":"Innovation in Aging","topic":"Geriatric Care and Nursing Homes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Dementia; Diversity (politics); Sociocultural evolution; Inclusion (mineral); Ethnic group; Public policy; Sexual orientation; Socioeconomic status; Population; Health policy; Political science; Economic growth; Health care; Gerontology; Sociology; Medicine; Gender studies; Economics; Demography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01700625,0.0003722214,0.0006014617,0.01602666,0.01687532,0.008461734,0.002195382,0.001211672,0.002990418],"category_scores_gemma":[0.07445829,0.0004026977,0.000660561,0.0362875,0.005480811,0.002935828,0.003273177,0.001643377,0.0001239205],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.308506,"about_ca_system_score_gemma":0.3958804,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9920681,"about_ca_topic_score_gemma":0.9899426,"domain_scores_codex":[0.9823574,0.002932781,0.001160329,0.0007464956,0.009254718,0.003548418],"domain_scores_gemma":[0.9168003,0.034463,0.006957322,0.001740321,0.03660881,0.003430235],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002946678,0.000224053,0.2641788,0.004670163,0.0002349722,0.001392571,0.2664559,0.003030517,0.0006236744,0.3009301,0.04210688,0.1158578],"study_design_scores_gemma":[0.00005807839,0.00006351505,0.388783,0.006113446,0.000318198,0.0002101694,0.3273387,0.002950091,0.0007371368,0.009115042,0.2641185,0.0001941445],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7111393,0.01353685,0.001256688,0.04042549,0.0001453175,0.0009179272,0.00928985,0.00005218354,0.2232364],"genre_scores_gemma":[0.9856616,0.006449433,0.001668912,0.002056497,0.00002699221,0.0002484343,0.001588011,0.00001754,0.002282727],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.691494,"threshold_uncertainty_score":0.802035,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04160668034273597,"score_gpt":0.3822247097301049,"score_spread":0.340618029387369,"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."}}