{"id":"W4309875846","doi":"10.1016/j.jmacro.2022.103483","title":"Macroeconomic effects of government spending shocks: New narrative evidence from Canada","year":2022,"lang":"en","type":"article","venue":"Journal of Macroeconomics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Government spending; Economics; Government (linguistics); Narrative; Principal (computer security); Macroeconomics; Construct (python library); Government revenue; Government budget; Monetary economics; Public finance; Welfare; Market economy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008181197,0.0002659954,0.00104517,0.0001595604,0.000178759,0.00005435919,0.0008048444,0.00005750991,0.003544397],"category_scores_gemma":[0.0001962837,0.0003353956,0.0003140772,0.00007950228,0.0000490936,0.0005863582,0.000250734,0.0004534544,0.00003568098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002929934,"about_ca_system_score_gemma":0.0003317035,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.3121527,"about_ca_topic_score_gemma":0.03256717,"domain_scores_codex":[0.9971766,0.00005384271,0.001924475,0.0003525338,0.00008816765,0.0004043655],"domain_scores_gemma":[0.9956897,0.0005522863,0.003083116,0.0003881328,0.000009087633,0.000277623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001287668,0.0002833825,0.7211714,0.0001778827,0.0022766,0.0001912698,0.01198668,0.1675546,0.0007175152,0.005169368,0.08460817,0.004575489],"study_design_scores_gemma":[0.01652341,0.004177386,0.5526443,0.0006080843,0.0004184845,0.0008087165,0.01355743,0.03338641,0.02977701,0.07924223,0.2647086,0.004147988],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902376,0.003958426,0.0003343568,0.001174207,0.002695345,0.0002006766,0.0006739234,0.000004506907,0.0007209754],"genre_scores_gemma":[0.9965948,0.0005295409,0.0009743745,0.0006661706,0.0004782683,0.000005661231,0.000005983802,0.00003771147,0.0007075146],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2795855,"threshold_uncertainty_score":0.9999098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03501423978011731,"score_gpt":0.2158086883711528,"score_spread":0.1807944485910355,"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."}}