{"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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0005632926,0.000137859,0.000257955,0.0004549322,0.0004623088,0.001488075,0.0003289116,0.0001212339,0.000003571441],"category_scores_gemma":[0.0004882156,0.000153097,0.00001850226,0.00006617489,0.0001833576,0.002005895,0.0001277265,0.0003484241,7.588018e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001509856,"about_ca_system_score_gemma":0.000537938,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002988114,"about_ca_topic_score_gemma":0.02249196,"domain_scores_codex":[0.9990491,0.00009223283,0.0003670083,0.0002426231,0.00005231789,0.0001967453],"domain_scores_gemma":[0.9991576,0.00009284167,0.0003241405,0.0001392922,0.000107948,0.0001781418],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000005238942,0.00001642735,0.9443836,0.0000145184,0.00003408725,0.00003626603,0.006709945,0.00002450088,0.0003274229,0.02552394,0.00005925797,0.02286477],"study_design_scores_gemma":[0.001693337,0.0004785472,0.9290379,0.0002047219,0.00000994735,0.0003506578,0.04890109,0.000813995,0.000741755,0.01545207,0.001855904,0.0004601113],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9733762,0.0001670667,0.0008484021,0.02523959,0.0001178057,0.000124626,0.00001531878,0.00002561024,0.00008544111],"genre_scores_gemma":[0.9983519,0.00005385621,0.001256763,0.0002093224,0.00005935847,0.000009858142,0.00001690447,0.00001159397,0.00003045918],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04219114,"threshold_uncertainty_score":0.9995485,"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."}}