{"id":"W4294969104","doi":"10.3390/admsci12030112","title":"Digital Divide: Barriers to Accessing Online Government Services in Canada","year":2022,"lang":"en","type":"article","venue":"Administrative Sciences","topic":"E-Government and Public Services","field":"Social Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Ryerson University","keywords":"Digital divide; Equity (law); Government (linguistics); Business; Bivariate analysis; Logit; Public economics; Welfare; Rural area; Universal design; Economic growth; Economics; The Internet; Computer science; Political science; Econometrics; World Wide Web","routes":{"ca_aff":true,"ca_fund":true,"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":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008410076,0.0001317393,0.0001533715,0.00004655463,0.001783992,0.000534298,0.001199055,0.00001811934,0.00167742],"category_scores_gemma":[0.0001698699,0.0001290865,0.00003008354,0.001264648,0.0003110178,0.001052853,0.000363577,0.0001451328,0.000003065682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001393705,"about_ca_system_score_gemma":0.005102231,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7204718,"about_ca_topic_score_gemma":0.9929504,"domain_scores_codex":[0.9962347,0.0001744694,0.0002533722,0.0004159117,0.002415596,0.0005059711],"domain_scores_gemma":[0.9991011,0.0002681179,0.0001471868,0.0001148606,0.00002755457,0.0003411709],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0000277085,0.00008367843,0.9551119,0.000009838687,0.00001272474,0.00003643861,0.0239269,0.0002952134,0.00003699807,0.006078223,0.001153785,0.01322658],"study_design_scores_gemma":[0.0001538548,0.0001872714,0.06422819,0.00002250825,0.000003882399,9.967902e-7,0.741033,0.0001318963,0.00009111221,0.0004222442,0.1934425,0.0002826126],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8910339,0.00006653503,0.00000184908,0.01827719,0.0004622597,0.0002087785,0.0003285596,0.00001853354,0.08960236],"genre_scores_gemma":[0.9951141,0.000005977955,0.00007293203,0.00322293,0.00008883316,0.00003481435,0.000008994,0.000004865416,0.00144659],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8908837,"threshold_uncertainty_score":0.9995155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03728099889971924,"score_gpt":0.330638157646225,"score_spread":0.2933571587465057,"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."}}