{"id":"W2499764404","doi":"10.15353/joci.v12i2.3240","title":"Enhancing Citizen Engagement with Open Government Data","year":2016,"lang":"en","type":"article","venue":"The Journal of Community Informatics","topic":"E-Government and Public Services","field":"Social Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"International Development Research Centre","keywords":"Open government; Government (linguistics); Civil society; Public relations; Order (exchange); Open data; Action (physics); Political science; Action research; Public administration; Business; Knowledge management; Sociology; Computer science; Pedagogy; Politics","routes":{"ca_aff":false,"ca_fund":true,"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":[0.01612817,0.0005304079,0.0005012985,0.001403058,0.003592954,0.00846916,0.001547402,0.002335788,0.006082893],"category_scores_gemma":[0.04577647,0.0003157805,0.0006597507,0.001715266,0.002690724,0.00962109,0.01844089,0.002254465,0.001271081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001773186,"about_ca_system_score_gemma":0.004034069,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001556278,"about_ca_topic_score_gemma":0.002230256,"domain_scores_codex":[0.9595486,0.03085543,0.0007125839,0.001667788,0.00396428,0.003251211],"domain_scores_gemma":[0.9421674,0.03976069,0.004020289,0.006049932,0.003507876,0.004493854],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004950345,0.004626715,0.1158471,0.001536052,0.000144283,0.001258251,0.3446527,0.002300567,0.01170193,0.03193492,0.006542565,0.4789598],"study_design_scores_gemma":[0.0002255422,0.003214478,0.07009847,0.001713678,0.000199663,0.001232361,0.4746217,0.01428305,0.01635659,0.07021724,0.3476573,0.0001797928],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.8360532,0.0003815462,0.03797749,0.01400387,0.00009808112,0.0008720701,0.0001492218,0.0003838969,0.1100808],"genre_scores_gemma":[0.9847505,0.0001754905,0.01045228,0.0005863234,0.00003586524,0.0002975138,0.00008355475,0.00003246222,0.00358596],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01612817,"threshold_uncertainty_score":0.0852949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1024993402899894,"score_gpt":0.3448127149241882,"score_spread":0.2423133746341988,"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."}}