{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01408355,0.00007646404,0.0001480207,0.00001707805,0.001056098,0.0002480097,0.005183249,0.00002839623,0.0002439482],"category_scores_gemma":[0.0002660477,0.00003456966,0.00001908904,0.0001195594,0.0002062122,0.002171326,0.001606461,0.0003607361,0.00001542518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001915857,"about_ca_system_score_gemma":0.0002183543,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008957405,"about_ca_topic_score_gemma":0.004174369,"domain_scores_codex":[0.9972485,0.0009793671,0.0004508126,0.000008778478,0.001131002,0.00018152],"domain_scores_gemma":[0.9968444,0.001450333,0.0007617907,0.0007299964,0.0001282935,0.00008516045],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.000278953,0.0001998303,0.001889493,0.00005778597,0.0003332059,7.273766e-7,0.8928901,0.0000136062,0.0001297049,0.01204361,0.02607856,0.06608441],"study_design_scores_gemma":[0.000561117,0.0001611315,0.0004722045,0.0001698606,0.00005451137,0.000006117504,0.6202619,0.000006399223,0.0002416049,0.0007088614,0.3772777,0.0000786157],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7000527,0.00004327722,0.00462173,0.02178044,0.000208885,0.0003339446,0.00004011745,0.0000148885,0.272904],"genre_scores_gemma":[0.9962251,0.0006299801,0.001074397,0.001360221,0.00009963988,8.137251e-7,0.000001713711,0.000005032206,0.0006031725],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3511991,"threshold_uncertainty_score":0.9631853,"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."}}