{"id":"W2017983121","doi":"10.1002/itdj.20018","title":"Infostates across countries and over time: Conceptualization, modeling, and measurements of the digital divide","year":2005,"lang":"en","type":"article","venue":"Information Technology for Development","topic":"ICT Impact and Policies","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Conceptualization; Digital divide; Computer science; Regional science; Data science; Econometrics; Knowledge management; Information and Communications Technology; Sociology; World Wide Web; Mathematics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.001750693,0.0001966494,0.0003531843,0.003400694,0.0008347025,0.00582026,0.0005914112,0.0008802925,0.00286166],"category_scores_gemma":[0.01111456,0.0001921791,0.0004669887,0.01259546,0.002642264,0.01127552,0.002580874,0.0009591449,0.0001631259],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002797296,"about_ca_system_score_gemma":0.001602151,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0245949,"about_ca_topic_score_gemma":0.01625025,"domain_scores_codex":[0.9991711,0.0003998952,0.00005323923,0.0001254371,0.000132588,0.0001177064],"domain_scores_gemma":[0.9936885,0.003550706,0.001578203,0.0004966969,0.0004377258,0.0002481804],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0002825098,0.000114131,0.4323648,0.000115897,0.0001425075,0.0001200313,0.009319534,0.03429248,0.0002755735,0.4767702,0.001832365,0.04436997],"study_design_scores_gemma":[0.00004316171,0.0002107028,0.4486991,0.0004722486,0.0002825118,0.000208615,0.04597013,0.109308,0.001359408,0.3662049,0.02716036,0.00008078717],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.965834,0.0006111911,0.007053783,0.001662204,0.000009490584,0.00001971783,0.001037088,0.00003665161,0.02373593],"genre_scores_gemma":[0.9985576,0.000193215,0.0006698684,0.00002936977,0.000002928702,0.0000147732,0.0002502189,0.000006606696,0.0002754677],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0245949,"threshold_uncertainty_score":0.04890347,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01122848972771213,"score_gpt":0.2338406802357415,"score_spread":0.2226121905080294,"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."}}