{"id":"W3151584765","doi":"10.1257/aer.20200146","title":"Signaling and Employer Learning with Instruments","year":2022,"lang":"en","type":"article","venue":"American Economic Review","topic":"Intergenerational and Educational Inequality Studies","field":"Social Sciences","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Norges Forskningsråd","keywords":"Construct (python library); Productivity; Economics; Labour economics; Economic growth; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000417364,0.00004488214,0.0001341336,0.00001573386,0.000653306,0.00001624684,0.00006248483,0.000002401363,0.0006519437],"category_scores_gemma":[0.00002764762,0.00004068228,0.00002027409,0.00005993197,0.0001457502,0.00006206259,0.00003941368,0.00006175495,0.00002418862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001196848,"about_ca_system_score_gemma":0.0001137547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001939353,"about_ca_topic_score_gemma":0.0002453842,"domain_scores_codex":[0.9994169,0.0001700081,0.000123398,0.0001155107,0.00007631908,0.00009784548],"domain_scores_gemma":[0.999759,0.0000508195,0.0001062222,0.00003556559,0.00001511126,0.0000333177],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003516205,0.0001136423,0.3821785,0.0002996186,0.0004062251,0.000002484778,0.02296093,0.00131109,0.00002484503,0.1614667,0.03395592,0.3972449],"study_design_scores_gemma":[0.00004069324,0.00008035544,0.0021931,0.00005516221,0.00001652631,0.000002474357,0.00728348,0.000009989171,0.000001687052,0.0001890883,0.9900209,0.0001064947],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9599209,0.007285739,0.000008193592,0.01673752,0.0001541626,0.0001936111,0.000004964336,0.0000226449,0.01567229],"genre_scores_gemma":[0.9813122,0.0129774,0.0002130814,0.003491369,0.0001097562,0.0001019366,0.000008268812,0.000004968519,0.001781016],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9560651,"threshold_uncertainty_score":0.7138327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03427280322638042,"score_gpt":0.3360172917900625,"score_spread":0.301744488563682,"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."}}