{"id":"W4388647936","doi":"10.3386/w31846","title":"Technology and Labor Displacement: Evidence from Linking Patents with Worker-Level Data","year":2023,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Firm Innovation and Growth","field":"Economics, Econometrics and Finance","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Displacement (psychology); Labour economics; Displaced workers; Business; Demographic economics; Economics; Psychology; Economic growth; Unemployment","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":[0.003417729,0.0002630722,0.0003265419,0.003462518,0.0005027403,0.001141853,0.0008370859,0.0006189903,0.005236757],"category_scores_gemma":[0.03719497,0.0001941696,0.0004206373,0.00737823,0.0007807639,0.001213111,0.001228314,0.000536667,0.001043821],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004967007,"about_ca_system_score_gemma":0.0005956957,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01733531,"about_ca_topic_score_gemma":0.01505079,"domain_scores_codex":[0.997503,0.0008778267,0.0002855819,0.0004304825,0.000672746,0.000230327],"domain_scores_gemma":[0.871121,0.06777676,0.05148397,0.005767788,0.002540115,0.001310322],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005967209,0.00005928015,0.9892299,0.00003603333,0.00006968708,0.00007083817,0.0001662694,0.0007992848,0.00009477324,0.000497905,0.0004184196,0.008497906],"study_design_scores_gemma":[0.00001453987,0.00008589924,0.9936106,0.00004175139,0.00005581782,0.00007775232,0.0003484288,0.001905408,0.0003343912,0.001149243,0.002361757,0.00001441988],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9852636,0.001647341,0.001773027,0.00061745,0.00001375723,0.00003403791,0.004438485,0.00003549642,0.006176882],"genre_scores_gemma":[0.9954561,0.0005946127,0.0004757672,0.00005974054,0.00003972548,0.00002537992,0.002460409,0.000005326419,0.0008829042],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01733531,"threshold_uncertainty_score":0.03446883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.74800430842551,"score_gpt":0.5171609937697341,"score_spread":0.2308433146557759,"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."}}