{"id":"W4317666880","doi":"10.48550/arxiv.2301.07855","title":"Digital Divide: Evidence from the 2020 Canadian Internet Use Survey","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"ICT Impact and Policies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"York University","keywords":"Digital divide; Digital literacy; The Internet; Inference; Literacy; Population; Data science; Computer science; Geography; World Wide Web; Economic growth; Sociology; Demography; Economics; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004273458,0.0005559826,0.0004937666,0.006570444,0.002969507,0.002525095,0.001961608,0.0006929348,0.007220762],"category_scores_gemma":[0.01480265,0.0002845866,0.0007513404,0.01972735,0.001248435,0.001303583,0.002285047,0.001056257,0.0009371928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02083402,"about_ca_system_score_gemma":0.02945829,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9940662,"about_ca_topic_score_gemma":0.9934022,"domain_scores_codex":[0.9956384,0.0003492272,0.0002166458,0.0004428734,0.002415954,0.0009369614],"domain_scores_gemma":[0.9796889,0.002492251,0.003271847,0.001056386,0.01123451,0.00225612],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001543715,0.00009057578,0.9249614,0.0002971386,0.0001647015,0.00009504072,0.001818885,0.0005034573,0.00005334444,0.004520356,0.03323142,0.03410922],"study_design_scores_gemma":[0.000009307827,0.00001514576,0.9766012,0.0001766005,0.00004860201,0.00002580652,0.00182782,0.000567271,0.0001009749,0.0002147405,0.0203857,0.00002679587],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6718332,0.01041592,0.001291782,0.008181839,0.0001772548,0.0002070766,0.2342227,0.0001229763,0.07354736],"genre_scores_gemma":[0.9209225,0.005104891,0.0007552275,0.001091896,0.00006710524,0.0001085307,0.06448361,0.00004515811,0.007421225],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02083402,"threshold_uncertainty_score":0.1511621,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1686814008011583,"score_gpt":0.1951537833737411,"score_spread":0.02647238257258286,"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."}}