{"id":"W2587642240","doi":"10.1177/2399654417691512","title":"Learning from community indicators movements: Towards a citizen-powered urban data revolution","year":2017,"lang":"en","type":"article","venue":"Environment and Planning C Politics and Space","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Enthusiasm; Deliberation; Political science; Democracy; Urban community; Corporate governance; Key (lock); Public relations; Sociology; Psychology; Computer science; Economics; Law; Computer security; Management","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0008634442,0.00009238885,0.0001340917,0.00004658523,0.003567537,0.0002201015,0.0003192735,0.00007980878,0.0001060273],"category_scores_gemma":[0.0003400611,0.00009689348,0.00001898974,0.00002108791,0.0004724358,0.0001748639,0.0002520634,0.0002640739,0.000005303962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005675401,"about_ca_system_score_gemma":0.00003500475,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04194135,"about_ca_topic_score_gemma":0.0004911663,"domain_scores_codex":[0.9989852,0.0002739285,0.0001182468,0.0002032254,0.0002038849,0.0002154873],"domain_scores_gemma":[0.9990652,0.0001302551,0.0001311206,0.0005132276,0.000005860358,0.0001543528],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000007732559,0.00006810845,0.9450568,0.00001444502,0.00008863564,0.000003167168,0.04476428,0.00003513675,0.00003059268,0.004155553,0.0007306468,0.005044913],"study_design_scores_gemma":[0.0003996037,0.00005817288,0.8438364,0.0000713926,0.00009183973,1.193571e-7,0.02651379,0.002733691,0.00001508095,0.003875973,0.1221433,0.0002605852],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918627,0.0004380682,0.0006687723,0.0008647089,0.00004660661,0.00008184181,0.00006836639,0.00001930205,0.005949709],"genre_scores_gemma":[0.9970783,0.0005614738,0.0001203806,0.00008672268,0.0001432082,0.000002451427,0.0002182172,0.000005561674,0.001783686],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1214127,"threshold_uncertainty_score":0.9977297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04841244329700163,"score_gpt":0.3054950266480558,"score_spread":0.2570825833510542,"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."}}