{"id":"W4412506909","doi":"10.3389/fsoc.2025.1593330","title":"Rethinking digital and AI inclusion: participatory and intersectionality-informed methods for disability and migrant justice","year":2025,"lang":"en","type":"article","venue":"Frontiers in Sociology","topic":"Digital Economy and Work Transformation","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Disability Prevention and Rehabilitation","funders":"Canada Excellence Research Chairs, Government of Canada","keywords":"Intersectionality; Sociology; Inclusion (mineral); Gender studies; Economic Justice; Social justice; Citizen journalism; Participatory action research; Disability studies; Social science; Political science; Anthropology; Law","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.09368921,0.001041696,0.0008978025,0.006857836,0.01499423,0.01426047,0.004106057,0.002745275,0.007273279],"category_scores_gemma":[0.05358151,0.0008337462,0.0009007659,0.003720344,0.04779612,0.01667843,0.0324633,0.004137585,0.0007293751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007010229,"about_ca_system_score_gemma":0.0127711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002486375,"about_ca_topic_score_gemma":0.005591675,"domain_scores_codex":[0.9103357,0.08205534,0.001140891,0.002222116,0.002808138,0.001437757],"domain_scores_gemma":[0.9159116,0.06899543,0.002537741,0.008242429,0.002745662,0.001567065],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00004870841,0.0001347234,0.001550857,0.0004411613,0.0000201221,0.0002941276,0.8351156,0.0001953336,0.0005757833,0.1063088,0.0008751112,0.05443975],"study_design_scores_gemma":[0.00005856042,0.0001523188,0.001721775,0.001889437,0.00003629849,0.0003394847,0.7234752,0.0007525529,0.001358567,0.1850226,0.08514213,0.00005108787],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3872428,0.008886615,0.3465572,0.04025199,0.0009598166,0.005164603,0.000290843,0.000334781,0.2103114],"genre_scores_gemma":[0.8731062,0.002195532,0.1077327,0.001725093,0.0001032435,0.004660457,0.00008761981,0.0001485708,0.01024053],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09368921,"threshold_uncertainty_score":0.4954818,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03655322966146657,"score_gpt":0.3916302457809757,"score_spread":0.3550770161195091,"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."}}