{"id":"W4413820711","doi":"10.2196/69373","title":"Representations of Older Adults’ Digital Literacy in Canadian News Media: Critical Discourse Analysis Using Unified Theory of Acceptance and Use of Technology 2","year":2025,"lang":"en","type":"article","venue":"JMIR Aging","topic":"Technology Use by Older Adults","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Social Sciences and Humanities Research Council of Canada; University of Ottawa","keywords":"Digital media; Inclusion (mineral); Narrative; Social media; Psychology; Literacy; Digital literacy; Public relations; Sociology; Internet privacy; Social psychology; Political science; Computer science; Pedagogy; World Wide Web","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0001918491,0.00007876567,0.0002851497,0.001669768,0.00008153144,0.00002890645,0.0002187206,0.0001470213,0.00001926764],"category_scores_gemma":[0.00178525,0.0000836344,0.00005607096,0.002886724,0.001185149,0.0004931606,0.0000784299,0.0001455692,1.155609e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006760833,"about_ca_system_score_gemma":0.0002770686,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.08798014,"about_ca_topic_score_gemma":0.3500806,"domain_scores_codex":[0.998944,0.00008098775,0.0003537629,0.0002306139,0.0001259772,0.0002647025],"domain_scores_gemma":[0.9988397,0.0005382396,0.0001079396,0.0002823822,0.0001700502,0.00006168552],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000102003,0.00005395557,0.9038506,0.0000362001,0.00006395203,0.000007982624,0.02617242,0.00002181186,0.00009187839,0.05236331,0.000009261585,0.01731848],"study_design_scores_gemma":[0.0006486389,0.00001349976,0.8610642,0.0007939627,0.0002389133,0.000001240867,0.1133794,0.0009167647,0.001161688,0.02146222,0.0001091029,0.0002103466],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961361,0.0001714102,0.0009918294,0.001979782,0.00004102808,0.0002091336,0.00004363474,0.00002794994,0.0003991568],"genre_scores_gemma":[0.9985783,0.0000201265,0.001318236,0.00002078358,0.000006072844,0.0000110035,0.000004192418,0.000004734622,0.0000365495],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2621005,"threshold_uncertainty_score":0.9180931,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01468128072123175,"score_gpt":0.3574700001843495,"score_spread":0.3427887194631178,"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."}}