{"id":"W2973078541","doi":"10.1016/j.ipm.2019.102111","title":"Immigrating after 60: Information experiences of older Chinese migrants to Australia and Canada","year":2019,"lang":"en","type":"article","venue":"Information Processing & Management","topic":"Technology Use by Older Adults","field":"Social Sciences","cited_by":67,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"University of South Australia","keywords":"Immigration; Family reunification; Population; Qualitative research; Coping (psychology); Sociology; Settlement (finance); Gender studies; Geography; Psychology; Demography; Social science; Business","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002633551,0.0001080954,0.0001203378,0.0002146041,0.0001661473,0.0001581133,0.0001981224,0.00005608132,0.00007625456],"category_scores_gemma":[0.00005174178,0.00009771432,0.00001497732,0.0003817711,0.00006454499,0.003262795,0.00008111115,0.00006164524,0.0000366111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008848459,"about_ca_system_score_gemma":0.00009941585,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1222679,"about_ca_topic_score_gemma":0.1384538,"domain_scores_codex":[0.9987923,0.0000160216,0.0004106552,0.00008646647,0.0004685524,0.0002260181],"domain_scores_gemma":[0.9994321,0.00001186033,0.0002309061,0.0001237611,0.0001379138,0.00006343835],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.00004416633,0.000019844,0.06043161,0.001039991,0.00002908909,0.00000187264,0.7579378,0.0001708522,0.000008148864,0.001170301,0.002246702,0.1768997],"study_design_scores_gemma":[0.000879488,0.00004482526,0.4853913,0.0005639324,0.00001959981,0.000001747829,0.4603041,0.0006100247,0.0002127178,0.0001875448,0.05131071,0.0004740231],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944835,0.00001281463,0.0005325046,0.0005256948,0.0002012183,0.0005624639,0.000003818609,0.00006538666,0.00361263],"genre_scores_gemma":[0.9979182,0.000004158176,0.001196299,0.0005103294,0.000009629138,0.0001091407,0.000007537803,0.000002527536,0.0002422],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4249597,"threshold_uncertainty_score":0.8835769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00468570842820317,"score_gpt":0.2541924854414541,"score_spread":0.2495067770132509,"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."}}