{"id":"W2764200494","doi":"","title":"2017-11 Different Paths? Human Capital Prices, Wages and Inequality in Canada and the US","year":2017,"lang":"en","type":"preprint","venue":"Econstor (Econstor)","topic":"Canadian Policy and Governance","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Productivity; Economics; Human capital; Labour economics; Inequality; Per capita; Capital (architecture); Capital deepening; Relative price; Demographic economics; Monetary economics; Capital formation; Macroeconomics; Financial capital; Economic growth; Population","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001128851,0.0003870502,0.0007649134,0.00009415845,0.001087261,0.0003588938,0.0007492449,0.0003040565,0.0001622298],"category_scores_gemma":[0.0005338888,0.0003296048,0.0001071562,0.0000409544,0.002215062,0.0001749445,0.0004972112,0.0007547716,0.000004190616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001407608,"about_ca_system_score_gemma":0.004054029,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9985273,"about_ca_topic_score_gemma":0.9999105,"domain_scores_codex":[0.9973842,0.0004047476,0.0005272499,0.0006813083,0.0003688233,0.0006336998],"domain_scores_gemma":[0.9975705,0.0004805027,0.0007461093,0.0007536882,0.00005022171,0.00039898],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001078382,0.00001692817,0.9545469,0.00007542045,0.0000410026,0.00004426858,0.006429031,0.000001267835,0.000001438433,0.03120487,0.007211812,0.000416291],"study_design_scores_gemma":[0.0008617218,0.000008494723,0.967261,0.0001577381,0.00003461568,0.000009458132,0.0007222447,0.000008132233,0.000004017232,0.005919823,0.0245313,0.0004814551],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9804369,0.003029241,6.477253e-7,0.004304986,0.00140386,0.0006362543,0.001124753,0.00001842838,0.009044996],"genre_scores_gemma":[0.9957155,0.001200888,0.000009055118,0.0006558535,0.0005398087,0.00007817825,0.00001318024,0.00001825418,0.001769308],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02528504,"threshold_uncertainty_score":0.9999156,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02403181596767457,"score_gpt":0.2725034504246918,"score_spread":0.2484716344570173,"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."}}