{"id":"W2754486029","doi":"10.1177/0309132517739142","title":"The geographies of social finance: Poverty regulation through the ‘invisible heart’ of markets","year":2017,"lang":"en","type":"article","venue":"Progress in Human Geography","topic":"Community Development and Social Impact","field":"Economics, Econometrics and Finance","cited_by":95,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Capitalism; Poverty; Geography of finance; Social studies of finance; Typology; Private finance initiative; Finance; Economics; Financial market; Sociology; Political science; Economic growth; Private sector","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":[0.0009877409,0.0001172671,0.0003121411,0.0001713744,0.001662488,0.0001666012,0.0007499001,0.00008566882,0.00004442168],"category_scores_gemma":[0.00005972919,0.00009104909,0.0002432903,0.0002949288,0.001111589,0.0003027341,0.0001963199,0.0001801102,0.000002014939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001261595,"about_ca_system_score_gemma":0.00001075823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004784294,"about_ca_topic_score_gemma":0.0002369358,"domain_scores_codex":[0.9989337,0.00005273211,0.0005373449,0.0001494819,0.0000798343,0.0002468833],"domain_scores_gemma":[0.9984846,0.00009298118,0.0007642886,0.0005891257,0.00005718773,0.0000118585],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002277451,0.00006747391,0.8674873,0.00002223994,0.00004965615,1.280274e-7,0.002103757,7.708601e-7,0.000001136132,0.1260597,0.000862996,0.003322064],"study_design_scores_gemma":[0.0002792564,0.00002626929,0.8497984,0.00002242475,0.000003985579,1.259596e-7,0.0001821997,0.00001620719,0.00003620835,0.1362712,0.01326994,0.00009371],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9768816,0.00558905,0.000006927025,0.001949719,0.0001864063,0.0002984031,0.00003093858,0.0000119321,0.01504504],"genre_scores_gemma":[0.999033,0.0006297747,0.0001202324,0.00003475329,0.00004038434,0.00003338342,0.000007189708,0.00001055743,0.00009074054],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0221514,"threshold_uncertainty_score":0.9996372,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03699715327290597,"score_gpt":0.2922064378095293,"score_spread":0.2552092845366233,"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."}}