{"id":"W3133661001","doi":"10.2139/ssrn.3757645","title":"Heterogeneous Labor Market Effects of Monetary Policy","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Economic Theory and Policy","field":"Economics, Econometrics and Finance","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Monetary policy; Economics; Monetary economics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002734932,0.0003419745,0.001186827,0.001123862,0.0007412996,0.003380815,0.0005629685,0.00177807,0.01954853],"category_scores_gemma":[0.0133298,0.0005201909,0.0005588559,0.0008630941,0.00127769,0.001934651,0.001312158,0.00175686,0.0007961088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001075075,"about_ca_system_score_gemma":0.0004751518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005043143,"about_ca_topic_score_gemma":0.004323415,"domain_scores_codex":[0.9993945,0.0002613039,0.00002543013,0.00008944794,0.00004054878,0.0001888403],"domain_scores_gemma":[0.9858807,0.01084864,0.001428246,0.0005933028,0.0002198709,0.001029273],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.009316289,0.00246437,0.1400809,0.0005458445,0.001044235,0.002685547,0.002350862,0.1328417,0.01091,0.6159374,0.01443028,0.06739264],"study_design_scores_gemma":[0.001904701,0.0008952103,0.2956624,0.0001604597,0.0009398567,0.0002453145,0.003654587,0.1539309,0.002570634,0.533977,0.005905349,0.0001536356],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9763799,0.0009060595,0.00263855,0.003505834,0.0001191292,0.00002641453,0.000466274,0.00005326624,0.01590445],"genre_scores_gemma":[0.9970089,0.0002603099,0.00009914788,0.000114435,0.00009277416,0.0000060423,0.00005390598,0.000006823545,0.002357692],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01954853,"threshold_uncertainty_score":0.06539637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007260247918984423,"score_gpt":0.1991187287582682,"score_spread":0.1918584808392838,"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."}}