{"id":"W3013941655","doi":"10.21125/inted.2020.1241","title":"REDEFINING THE DIGITAL DIVIDE IN THE AGE OF AI","year":2020,"lang":"en","type":"article","venue":"INTED proceedings","topic":"ICT Impact and Policies","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Digital divide; Media studies; World Wide Web; Sociology; The Internet","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007427445,0.00007340935,0.00008521396,0.00002682066,0.000020614,0.0000897158,0.0002301862,0.0000292942,0.000007921162],"category_scores_gemma":[0.0001682637,0.00004199317,0.0000323695,0.0002669441,0.0000382277,0.0001249603,0.00002840535,0.0002264813,0.00001351598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008116644,"about_ca_system_score_gemma":0.000004498287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001781679,"about_ca_topic_score_gemma":0.000001415012,"domain_scores_codex":[0.9996035,0.000001644295,0.0001287491,0.00002949317,0.00009818391,0.0001384497],"domain_scores_gemma":[0.9998595,0.00005207873,0.00001572884,0.00003788507,0.00001726061,0.00001761301],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005370567,0.00002857676,0.03395777,0.0003530351,0.0000960419,0.000007791202,0.7445874,0.0006048869,0.04878454,0.01927041,0.1429064,0.009349426],"study_design_scores_gemma":[0.001337302,0.0006082718,0.05211657,0.00070207,0.00008520682,0.00008368267,0.09428429,0.01410237,0.08516718,0.006000524,0.7444566,0.001055876],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9393482,0.00007582402,0.00004894878,0.005010635,0.00004128619,0.00007797395,0.000005974631,0.00009134487,0.05529984],"genre_scores_gemma":[0.9985567,0.000005758699,0.000004846634,0.001290024,0.00009777827,0.000005727593,0.000001969535,0.00001191164,0.00002527531],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6503032,"threshold_uncertainty_score":0.1712432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02044022261120352,"score_gpt":0.2343273862024049,"score_spread":0.2138871635912014,"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."}}