{"id":"W2585497290","doi":"10.21432/t21k7t","title":"A Connected Generation? Digital Inequalities in Elementary and High School Students According to Age and Socioeconomic Level | Une génération connectée? Inégalités numériques chez les élèves du primaire et du secondaire selon l’âge et le milieu socioéconomique","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Learning and Technology","topic":"Digital literacy in education","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Université du Québec à Montréal","funders":"","keywords":"Socioeconomic status; Humanities; Mathematics; Sociology; Demography; Population; Philosophy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0003854386,0.0001635275,0.0002649273,0.001240024,0.001406295,0.001548347,0.0004366954,0.0004794087,0.005210596],"category_scores_gemma":[0.0009584653,0.0001669933,0.0003124883,0.001593012,0.000939357,0.0008510472,0.0009655701,0.000465012,0.0003109424],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002132889,"about_ca_system_score_gemma":0.001404594,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5432516,"about_ca_topic_score_gemma":0.6912006,"domain_scores_codex":[0.9996336,0.00005062031,0.00001529903,0.0000738097,0.00006614676,0.0001606369],"domain_scores_gemma":[0.9992216,0.0001328673,0.0002303371,0.00004612228,0.0001356353,0.0002333743],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002663786,0.00003684638,0.9917132,0.00000893867,0.00001319209,0.00006365378,0.004925073,0.00001536093,0.000195541,0.0001894598,0.00008587456,0.002726282],"study_design_scores_gemma":[7.896764e-7,0.00001394508,0.9945996,0.000007083925,0.000004222665,0.00001651102,0.004952596,0.00003992831,0.00002671735,0.00002553558,0.0003102974,0.00000270265],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989703,0.0001006443,0.00003513588,0.00008615784,0.000002067357,0.000005320105,0.0001425047,8.084993e-7,0.0006571339],"genre_scores_gemma":[0.9993451,0.00005682362,0.0000227893,0.00002088553,0.000002259528,0.000004034776,0.00006334583,7.230216e-7,0.000484026],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4567484,"threshold_uncertainty_score":0.9188765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01682079788952168,"score_gpt":0.267679092850709,"score_spread":0.2508582949611873,"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."}}