{"id":"W7008674968","doi":"","title":"A Connected Generation? Digital Inequalities in Elementary and High School Students According to Age and Socioeconomic Level ----------
\\n
\\nUne génération connectée ? Inégalités numériques chez les élèves du primaire et du secondaire selon l’âge et le milieu socioéconomique","year":2016,"lang":"fr","type":"other","venue":"Archipelago (University of Quebec in Montreal)","topic":"Gender and Technology in Education","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Socioeconomic status; Relation (database); Inequality; Population","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001062712,0.0004956814,0.0008546548,0.0007144366,0.0005461026,0.0001876579,0.0005394564,0.0006315675,0.0005268489],"category_scores_gemma":[0.0001496291,0.0006195836,0.0001146073,0.0001863225,0.00108821,0.001348666,0.000436764,0.0005072144,0.00002506515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006738847,"about_ca_system_score_gemma":0.0006818146,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5345884,"about_ca_topic_score_gemma":0.9818818,"domain_scores_codex":[0.9969005,0.0008974004,0.0005956951,0.0008739033,0.0002187331,0.0005137864],"domain_scores_gemma":[0.9983966,0.0005017028,0.000505748,0.000290162,0.00009747234,0.000208265],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001279825,0.0003804635,0.6333061,0.0001548659,0.0002498999,0.00003630302,0.2478534,0.00003435465,0.0003304857,0.04599309,0.0004813792,0.07105158],"study_design_scores_gemma":[0.001876625,0.0000982253,0.6242825,0.0002083014,0.00003400464,0.000004182716,0.3502276,0.00006769362,0.00003070532,0.02243191,0.0002643703,0.000473968],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9772245,0.0002767122,0.0004355986,0.01635646,0.0002212761,0.001149487,0.0003832424,0.00008188586,0.003870877],"genre_scores_gemma":[0.9909809,0.001478104,0.000501173,0.0003137391,0.0001568732,0.00002104739,0.000356113,0.00006504064,0.006127071],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4472934,"threshold_uncertainty_score":0.9996256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01835101313344744,"score_gpt":0.2495357106386334,"score_spread":0.2311846975051859,"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."}}