{"id":"W2472937649","doi":"10.17645/up.v1i2.645","title":"Data-Driven Participation: Algorithms, Cities, Citizens, and Corporate Control","year":2016,"lang":"en","type":"article","venue":"Urban Planning","topic":"Smart Cities and Technologies","field":"Engineering","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Social Sciences and Humanities Research Council of Canada; Mitacs","keywords":"Praxis; Vision; Citizen journalism; Participatory democracy; Volunteered geographic information; Sociology; Civic engagement; Democracy; Rhetoric; Public relations; Public administration; Political science; Computer science; Data science; Politics; World Wide Web; Law","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.02214649,0.0005933136,0.0005422488,0.002235265,0.006330277,0.01653388,0.001912508,0.003510207,0.005025816],"category_scores_gemma":[0.02887503,0.0003258904,0.0004652962,0.004035075,0.05072455,0.01639301,0.008182885,0.004430405,0.0004869558],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008024965,"about_ca_system_score_gemma":0.006468259,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01678903,"about_ca_topic_score_gemma":0.01260615,"domain_scores_codex":[0.9852874,0.009785352,0.0003746525,0.00145725,0.002216213,0.0008789963],"domain_scores_gemma":[0.9701822,0.02153754,0.001592399,0.003787989,0.001853844,0.001045936],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001616114,0.00001443176,0.001465555,0.00005809614,0.000008145994,0.00004492037,0.01402886,0.00125461,0.0001400394,0.9704514,0.001191324,0.01132645],"study_design_scores_gemma":[0.00001831901,0.00002680491,0.001511691,0.0002499207,0.00001075206,0.00007835947,0.02282711,0.005504378,0.0006464299,0.8310959,0.1379942,0.00003604578],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1486836,0.005319499,0.2959802,0.1450071,0.0005414847,0.0002375274,0.0002331121,0.0002789389,0.4037185],"genre_scores_gemma":[0.9753534,0.000960507,0.01414403,0.001482277,0.0001521187,0.0001400822,0.00007453799,0.00009959496,0.007593452],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02214649,"threshold_uncertainty_score":0.1171232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05567254627023674,"score_gpt":0.2434355783320492,"score_spread":0.1877630320618124,"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."}}