{"id":"W2182839087","doi":"","title":"ASYMMETRIC TECHNOLOGICAL CHANGE IN THE MELITZ MODEL: ARE FOREIGN TECHNOLOGICAL IMPROVEMENTS HARMFUL?","year":2014,"lang":"en","type":"preprint","venue":"Carleton University's Institutional Repository (MacOdrum Library, Carleton University)","topic":"Fiscal Policy and Economic Growth","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Welfare; Homogeneous; Technological change; Economics; Elasticity of substitution; Microeconomics; International trade; Econometrics; Macroeconomics; Production (economics); Mathematics; Market economy","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":[0.001724973,0.0007094368,0.00118833,0.0007826907,0.0008002235,0.002600508,0.001047271,0.001968053,0.009115945],"category_scores_gemma":[0.003602608,0.0002427095,0.001192897,0.0008421672,0.0023819,0.003198587,0.001771248,0.002023797,0.0005574679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001751296,"about_ca_system_score_gemma":0.0007770472,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003511834,"about_ca_topic_score_gemma":0.003688093,"domain_scores_codex":[0.9994561,0.0002054517,0.00002242113,0.0001028085,0.00006116243,0.0001520666],"domain_scores_gemma":[0.9982355,0.0007897794,0.0004491956,0.0002688789,0.00009516365,0.0001614188],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002193257,0.0001203188,0.003627896,0.00009895738,0.00007692329,0.0003692737,0.0002264228,0.1161258,0.001413836,0.8596781,0.00261393,0.01542927],"study_design_scores_gemma":[0.000103454,0.00009391971,0.00213578,0.00003295088,0.00008112485,0.0001247399,0.0002497135,0.2246773,0.0006446207,0.7685459,0.003273102,0.00003733304],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6566787,0.001271045,0.210135,0.009056462,0.0002357664,0.00009484855,0.0005467086,0.000246633,0.1217348],"genre_scores_gemma":[0.9828279,0.0007641185,0.004064358,0.0003485211,0.00008750409,0.00003722063,0.00007180201,0.00002702933,0.01177149],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009115945,"threshold_uncertainty_score":0.03049582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03616538196269849,"score_gpt":0.1930961013978717,"score_spread":0.1569307194351732,"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."}}