{"id":"W2518186030","doi":"10.3138/cpp.2014-070","title":"Targeting Tax Relief at Youth Employment","year":2016,"lang":"en","type":"article","venue":"Canadian Public Policy","topic":"Gender, Labor, and Family Dynamics","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Subsidy; Earnings; Unemployment; Labour economics; Youth unemployment; Demographic economics; Economics; Displacement (psychology); Unemployment rate; Difference in differences; Economic growth; Psychology; Finance","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.0008627586,0.0001672424,0.0001931082,0.0007781664,0.001795299,0.0008009551,0.0007454413,0.0005880418,0.005266038],"category_scores_gemma":[0.0020977,0.0001314137,0.0003760669,0.0007307683,0.0005284129,0.0002355363,0.0008957838,0.0009208799,0.0003342706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01279819,"about_ca_system_score_gemma":0.04612659,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.8756948,"about_ca_topic_score_gemma":0.9470556,"domain_scores_codex":[0.9982247,0.0001858785,0.00001539445,0.00006979165,0.0004033732,0.00110089],"domain_scores_gemma":[0.9991326,0.00008557067,0.00008534109,0.00003154424,0.0002275591,0.0004372696],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001016606,0.001616346,0.2597367,0.0006636697,0.0002019233,0.0008221403,0.004256583,0.006571295,0.008411978,0.05752611,0.2226243,0.4365524],"study_design_scores_gemma":[0.0004927131,0.0007452811,0.7129685,0.0006294694,0.0001829627,0.000324742,0.005916544,0.004683614,0.004559676,0.003267774,0.266169,0.00005964475],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8295056,0.004357248,0.002855804,0.01735994,0.0004463994,0.0007883549,0.005117571,0.0002237338,0.1393454],"genre_scores_gemma":[0.967256,0.001426284,0.001232961,0.002970108,0.00006828847,0.0001504307,0.0007493144,0.00001495803,0.02613178],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8756948,"threshold_uncertainty_score":0.2500744,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02852532067005525,"score_gpt":0.2672817557107483,"score_spread":0.238756435040693,"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."}}