{"id":"W2529697177","doi":"10.2139/ssrn.2882630","title":"How to Improve Inflation Targeting in Canada","year":2016,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Bank of Canada; Government of Canada","funders":"","keywords":"Economics; Monetary policy; Inflation targeting; Interest rate; Monetary economics; Transparency (behavior); Zero lower bound; Real interest rate; Stimulus (psychology); Forward guidance; Nominal interest rate; Inflation (cosmology); Fiscal policy; Macroeconomics; Credit channel; Computer science","routes":{"ca_aff":true,"ca_fund":false,"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":[0.004221383,0.0003964508,0.0005294651,0.002036849,0.005033524,0.004981757,0.001270345,0.002760901,0.008824136],"category_scores_gemma":[0.02003436,0.0003210097,0.0006357075,0.002851734,0.0009520734,0.001595166,0.0017286,0.002937047,0.0009263699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06656346,"about_ca_system_score_gemma":0.2958411,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9917166,"about_ca_topic_score_gemma":0.9925334,"domain_scores_codex":[0.9944,0.00065336,0.0002418315,0.0003560928,0.002076372,0.002272376],"domain_scores_gemma":[0.9878154,0.0008745997,0.0005984289,0.0002714786,0.007771217,0.002668916],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005534355,0.0003508221,0.07604288,0.0005879964,0.0003168191,0.0006343536,0.002505872,0.02806482,0.002705364,0.08608821,0.4165447,0.3856047],"study_design_scores_gemma":[0.0005186168,0.0002778334,0.2666866,0.001005393,0.000596657,0.0003180303,0.005933014,0.04371704,0.005570096,0.0266875,0.6482869,0.0004024204],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2571528,0.01284129,0.01109522,0.5054637,0.00324911,0.0004562432,0.003782,0.001584583,0.204375],"genre_scores_gemma":[0.9120387,0.00378634,0.01061012,0.02892692,0.0004771731,0.00009500093,0.000877303,0.0002250741,0.04296336],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06656346,"threshold_uncertainty_score":0.482954,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01479156758228887,"score_gpt":0.1814744833324139,"score_spread":0.166682915750125,"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."}}