{"id":"W4414192481","doi":"10.3386/w34236","title":"Tariffs, Manufacturing Employment, and Supply Chains","year":2025,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Labor Movements and Unions","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Downstream (manufacturing); Upstream (networking); Supply chain; Manufacturing sector; Manufacturing; Upstream and downstream (DNA)","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":[0.0008680207,0.0005612235,0.0004983943,0.0008410052,0.0007839971,0.002208789,0.0008881976,0.001521219,0.01621389],"category_scores_gemma":[0.004587438,0.0004964501,0.0007350886,0.001664557,0.001241986,0.00238901,0.001182596,0.001200399,0.0008767801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002813783,"about_ca_system_score_gemma":0.00154205,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01663836,"about_ca_topic_score_gemma":0.01364648,"domain_scores_codex":[0.9996071,0.000129064,0.00001363479,0.00005274586,0.00006514884,0.0001322537],"domain_scores_gemma":[0.9984236,0.0009166535,0.000337166,0.00007806743,0.0001008425,0.0001437307],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002032859,0.0001574385,0.00834031,0.00009995265,0.0000673759,0.000253652,0.0001399064,0.7983831,0.0004846968,0.1795168,0.001880255,0.01047319],"study_design_scores_gemma":[0.0002565625,0.0002061514,0.005355719,0.0001022579,0.00006477853,0.000125147,0.0004628956,0.5790806,0.00040164,0.4064654,0.007428429,0.00005030477],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8181578,0.002768201,0.08250572,0.007208513,0.0001848243,0.0001540317,0.0013064,0.0002914982,0.08742305],"genre_scores_gemma":[0.9867471,0.0009970868,0.001854097,0.0001261752,0.00002990745,0.00003179169,0.0001619598,0.0000181388,0.01003367],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01663836,"threshold_uncertainty_score":0.05424088,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2837836738981556,"score_gpt":0.5326835144174471,"score_spread":0.2488998405192915,"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."}}