{"id":"W4255775825","doi":"10.32920/ryerson.14636280","title":"How connected are Canadians? Inequities in Canadian households' internet access","year":2021,"lang":"en","type":"preprint","venue":"","topic":"E-Government and Public Services","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"The Internet; Notice; Demographic economics; Internet access; Business; Internet users; Economic growth; Economics; Political science; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009294669,0.0002739498,0.0003747629,0.002759267,0.006375766,0.003520229,0.001067553,0.0005359897,0.007333313],"category_scores_gemma":[0.00442343,0.0001885431,0.0004191128,0.01024663,0.001772581,0.001710869,0.00161731,0.0009061038,0.0002634824],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03276028,"about_ca_system_score_gemma":0.03451471,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9975291,"about_ca_topic_score_gemma":0.997754,"domain_scores_codex":[0.9987059,0.00008662866,0.00003372826,0.0001624061,0.0003935241,0.0006179566],"domain_scores_gemma":[0.9975262,0.0002461631,0.0003561566,0.0001023923,0.001096054,0.0006729905],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001873743,0.00005728955,0.7927833,0.000342443,0.0001953993,0.0003688845,0.04047619,0.0007255459,0.0004215484,0.03160521,0.0302379,0.1025988],"study_design_scores_gemma":[0.0000104498,0.00002112945,0.9035248,0.0003837499,0.00008576937,0.0001274582,0.06284043,0.0007538975,0.0001639596,0.001742904,0.0302715,0.00007389806],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9086307,0.004743388,0.0004330036,0.01535694,0.00008562993,0.00003562632,0.009350658,0.00003368155,0.06133043],"genre_scores_gemma":[0.9950219,0.001761304,0.0001505901,0.0004354872,0.0000108398,0.000006609409,0.0009760449,0.000009635416,0.00162761],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03276028,"threshold_uncertainty_score":0.2376935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05912564976272633,"score_gpt":0.2966636039612904,"score_spread":0.237537954198564,"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."}}