{"id":"W7133537795","doi":"10.21916/mlr.2026.6","title":"Is manufacturing productivity recovering? Evidence from the past and present","year":2013,"lang":"","type":"article","venue":"Monthly labor review","topic":"Economic Growth and Productivity","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Productivity; Business cycle; Manufacturing sector; Manufacturing","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004646611,0.0003205142,0.0005210752,0.004068835,0.0007037793,0.003467002,0.001269002,0.001460608,0.01058793],"category_scores_gemma":[0.02454035,0.0003433207,0.0007140567,0.007384634,0.002323192,0.003819556,0.001664252,0.002755871,0.002156961],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001939418,"about_ca_system_score_gemma":0.001407921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01693845,"about_ca_topic_score_gemma":0.01176576,"domain_scores_codex":[0.9978727,0.0003058404,0.0002719928,0.0004780415,0.0005872849,0.0004840844],"domain_scores_gemma":[0.9677896,0.009682945,0.01361628,0.002509335,0.00504479,0.001357057],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001160356,0.0002269431,0.6458868,0.002813182,0.0009096031,0.001185739,0.002428989,0.001005418,0.0006827419,0.01709636,0.0388913,0.2877126],"study_design_scores_gemma":[0.00003797615,0.0001666811,0.8893223,0.001733035,0.0004231287,0.0006217336,0.00440978,0.0003318636,0.0007364465,0.005450998,0.0967109,0.0000551478],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.620299,0.1728361,0.00187137,0.1254313,0.001223145,0.00003836837,0.01674631,0.0001364851,0.06141792],"genre_scores_gemma":[0.9369513,0.05109612,0.0002693109,0.00369126,0.001572504,0.00001018829,0.004512609,0.00002989856,0.001866748],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01693845,"threshold_uncertainty_score":0.03542018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04279710192693011,"score_gpt":0.2333344257879549,"score_spread":0.1905373238610247,"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."}}