{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003024631,0.0001515025,0.000244038,0.001229852,0.0008394983,0.001603015,0.0004656992,0.0004377511,0.007981023],"category_scores_gemma":[0.001422039,0.0001801779,0.0003685039,0.001585481,0.0007223216,0.0009254427,0.001394571,0.0004512272,0.0004062561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001230746,"about_ca_system_score_gemma":0.001040708,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2495529,"about_ca_topic_score_gemma":0.424318,"domain_scores_codex":[0.9997172,0.00003738114,0.00001283786,0.00007010368,0.00004573041,0.0001166771],"domain_scores_gemma":[0.9991284,0.0001583501,0.0002676758,0.00006397483,0.0001223121,0.000259373],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004353047,0.00004192257,0.989554,0.00001553067,0.00002638202,0.0000820797,0.003587093,0.00003569539,0.0001878705,0.0007935811,0.0001371126,0.005495314],"study_design_scores_gemma":[0.000001408612,0.00001967265,0.9953672,0.0000163137,0.00001183931,0.00002223386,0.003698779,0.00007252479,0.00004335372,0.0001165759,0.0006269483,0.000003133882],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978687,0.0002636981,0.00005159514,0.0001853913,0.00000396506,0.000005467125,0.0002116502,0.000001655997,0.001407971],"genre_scores_gemma":[0.9986271,0.0001600857,0.00002960847,0.00002587798,0.000003939402,0.00000466375,0.00009196974,0.000001517475,0.001055309],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7504471,"threshold_uncertainty_score":0.4962007,"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."}}