{"id":"W4294549706","doi":"10.1007/s12134-022-00983-w","title":"Immigrant Identifications and ICT Use: A Survey Study of Chinese and South Asian Immigrants in Canada","year":2022,"lang":"en","type":"article","venue":"Journal of International Migration and Integration / Revue de l integration et de la migration internationale","topic":"Diaspora, migration, transnational identity","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"National Cancer Centre of Singapore","keywords":"Immigration; Information and Communications Technology; Dual (grammatical number); Identity (music); Exploratory research; Settlement (finance); Identification (biology); Economic growth; Political science; Sociology; Business; Social science; Economics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.004490059,0.0002880145,0.0004296308,0.001172595,0.0003976845,0.0005066434,0.0004151931,0.0001030557,0.0001825508],"category_scores_gemma":[0.003299992,0.0002957729,0.00009604181,0.0007433292,0.0001893495,0.001921637,0.00007333981,0.0006567388,5.881284e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001482736,"about_ca_system_score_gemma":0.001706599,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7386078,"about_ca_topic_score_gemma":0.9883692,"domain_scores_codex":[0.9944679,0.002105413,0.001575397,0.0003988271,0.00122032,0.0002322177],"domain_scores_gemma":[0.9953498,0.001336594,0.001328075,0.0001743414,0.001626968,0.0001842326],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003188024,0.0006192699,0.8892981,0.00001287298,0.0001157047,0.00001554529,0.07370152,0.001685582,0.002200189,0.03021589,0.000528556,0.001287945],"study_design_scores_gemma":[0.001345213,0.0002612634,0.9384754,0.00008238648,0.000034614,0.0001165373,0.0465548,0.008664149,0.0001152059,0.001708244,0.002396647,0.0002454912],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9870617,0.0001854347,0.005774649,0.005149901,0.0005495218,0.0005734722,0.0002632945,0.00001803343,0.0004240165],"genre_scores_gemma":[0.9965549,0.000933763,0.000911885,0.0004151941,0.0001267236,0.0001100143,0.0002703763,0.00002636445,0.0006508277],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2497614,"threshold_uncertainty_score":0.9999495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02519506695193858,"score_gpt":0.3139798066825988,"score_spread":0.2887847397306603,"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."}}