{"id":"W2609012786","doi":"10.15353/joci.v13i1.3300","title":"Developing Social Alongside Technical Infrastructure: A Case Study Applying ICTD Tenets to Marginalized Communities in the United States","year":2017,"lang":"en","type":"article","venue":"The Journal of Community Informatics","topic":"Innovative Approaches in Technology and Social Development","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agency (philosophy); Equity (law); Public relations; Psychological intervention; Sociology; Ethnography; Participatory design; Citizen journalism; Community health workers; Context (archaeology); Product (mathematics); Process (computing); Economic growth; Political science; Engineering; Social science; Computer science; Economics; Population; Health services; Medicine; Nursing; Geography; Operations management","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.003923466,0.000494781,0.0004526942,0.00164098,0.01931946,0.003504661,0.00161459,0.002206954,0.002314743],"category_scores_gemma":[0.005619535,0.0004163972,0.0003665387,0.001179149,0.00865451,0.00250726,0.009264099,0.002056358,0.0001524582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004533204,"about_ca_system_score_gemma":0.008626294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03638059,"about_ca_topic_score_gemma":0.1031797,"domain_scores_codex":[0.9957269,0.002963848,0.00008355325,0.0002034827,0.0002741984,0.0007480261],"domain_scores_gemma":[0.9967194,0.001693792,0.0002384547,0.0002378823,0.0002991069,0.0008113319],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00006058197,0.0009317128,0.01466447,0.0001915902,0.00002032443,0.009280487,0.9336739,0.0003173266,0.00144427,0.007504645,0.001027145,0.03088346],"study_design_scores_gemma":[0.00000991873,0.0002512041,0.003813228,0.0001187568,0.00001152525,0.0008520858,0.9828587,0.0003934352,0.0003841791,0.001107829,0.01018801,0.00001124916],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908946,0.0001528837,0.00122493,0.001141992,0.00001666065,0.0001434917,0.00001340002,0.00001200004,0.006400243],"genre_scores_gemma":[0.9970387,0.0001950383,0.001412024,0.0002449541,0.000005154144,0.00007670147,0.00000791507,0.000006387424,0.001013106],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03638059,"threshold_uncertainty_score":0.07233769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08730280733213805,"score_gpt":0.3249181827981905,"score_spread":0.2376153754660524,"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."}}