{"id":"W3014016081","doi":"10.1080/24694452.2020.1749023","title":"Green Structural Adjustment in the World Bank’s Resilient City","year":2020,"lang":"en","type":"article","venue":"Annals of the American Association of Geographers","topic":"Housing, Finance, and Neoliberalism","field":"Economics, Econometrics and Finance","cited_by":131,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; Vetenskapsrådet; Association of American Geographers","keywords":"Restructuring; Finance; Structural adjustment; Climate Finance; Investment (military); Poverty; Economics; Government (linguistics); Financial crisis; Urbanization; Critical infrastructure; Business; Economic growth; Developing country; Market economy; Political science; Macroeconomics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.001912854,0.0001617604,0.000110565,0.001015449,0.004818413,0.005543507,0.0003454835,0.00136611,0.004887743],"category_scores_gemma":[0.003578388,0.0001820702,0.0001123747,0.002802055,0.007851961,0.002743669,0.002934451,0.002454035,0.0002019534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009391312,"about_ca_system_score_gemma":0.006366939,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03098501,"about_ca_topic_score_gemma":0.05490149,"domain_scores_codex":[0.9988973,0.000572101,0.00002596595,0.00008405479,0.0001555282,0.0002650346],"domain_scores_gemma":[0.9987254,0.0005109731,0.0002239466,0.0001183327,0.00015139,0.0002699537],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00002515859,0.00006119034,0.007021739,0.00005052482,0.000007498138,0.0003195299,0.04386355,0.0009701299,0.000273407,0.8685564,0.05109669,0.02775429],"study_design_scores_gemma":[0.00001278242,0.00002463225,0.0239035,0.0002660133,0.000005676862,0.00006710034,0.03403072,0.0007620124,0.0003543766,0.07324712,0.8672837,0.00004236682],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3384576,0.004776102,0.003956648,0.1837044,0.0004530782,0.00008612576,0.0004336691,0.0001349578,0.4679974],"genre_scores_gemma":[0.970788,0.002193161,0.001528832,0.007605092,0.00007653272,0.00006306046,0.00007617897,0.00003783279,0.01763138],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03098501,"threshold_uncertainty_score":0.06813902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03791042674934327,"score_gpt":0.2630826451383517,"score_spread":0.2251722183890085,"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."}}