{"id":"W4229808178","doi":"10.32920/ryerson.14667915.v1","title":"Accessing Informal and Formal Social Supports Among Older Immigrants in Toronto: A Mixed-Methods Approach","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; Statistics Canada","funders":"","keywords":"Loneliness; Immigration; Qualitative research; Geospatial analysis; Social isolation; Receipt; Population; Mandarin Chinese; Geography; Sociology; Gerontology; Psychology; Medicine; Social psychology; World Wide Web; Computer science; Demography; Social science; Linguistics","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":[0.008766375,0.0009262806,0.001077482,0.003581111,0.006945091,0.002807406,0.001914295,0.001067071,0.004753039],"category_scores_gemma":[0.008665657,0.0009115422,0.001175852,0.004358612,0.001924824,0.001407165,0.004727875,0.001172629,0.0003429833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0234408,"about_ca_system_score_gemma":0.02353973,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6087529,"about_ca_topic_score_gemma":0.7786098,"domain_scores_codex":[0.9959629,0.002068733,0.0003801667,0.0004030694,0.0004632697,0.0007218925],"domain_scores_gemma":[0.9954275,0.002327945,0.0005381496,0.0002663312,0.001059696,0.0003804533],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0004316632,0.001398943,0.1581478,0.004286272,0.0003912395,0.001768173,0.7791403,0.0006564986,0.001269232,0.003527021,0.002930449,0.04605231],"study_design_scores_gemma":[0.0001431314,0.001171001,0.1379075,0.002895364,0.0004990991,0.0002452982,0.8436239,0.001109041,0.000684411,0.001881255,0.009744764,0.00009511031],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9826864,0.0022794,0.002522978,0.0005839103,0.0000433149,0.006582495,0.001747548,0.00001590663,0.003538052],"genre_scores_gemma":[0.9658451,0.003286424,0.009434456,0.001081599,0.00004399884,0.01506228,0.001307151,0.00002243541,0.003916491],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3912471,"threshold_uncertainty_score":0.7871025,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02834262890115963,"score_gpt":0.4079178514585242,"score_spread":0.3795752225573645,"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."}}