{"id":"W1564213895","doi":"","title":"Offshoring and Employment in Canada: Some Basic Facts","year":2007,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Global trade and economics","field":"Economics, Econometrics and Finance","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Offshoring; Stylized fact; Outsourcing; Layoff; Variety (cybernetics); Labour economics; Business; Set (abstract data type); Economics; Demographic economics; Unemployment; Marketing; Economic growth; Macroeconomics; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001198989,0.0004691402,0.0007534419,0.003674677,0.002725649,0.002782253,0.001212567,0.0006178931,0.004144889],"category_scores_gemma":[0.006716064,0.0002742689,0.0006824034,0.01530449,0.001543086,0.0009109101,0.001423647,0.001034427,0.0003466638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01064491,"about_ca_system_score_gemma":0.0134094,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9841585,"about_ca_topic_score_gemma":0.9880112,"domain_scores_codex":[0.9985226,0.0001131356,0.0001083733,0.0002257205,0.0006087085,0.0004214966],"domain_scores_gemma":[0.995617,0.001296341,0.001080052,0.0004740846,0.001150999,0.0003814277],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001656401,0.00005572317,0.9275057,0.0002505841,0.0002385711,0.0005136595,0.002612596,0.006105884,0.0004970517,0.01593835,0.01113088,0.03498541],"study_design_scores_gemma":[0.00001485658,0.00002869973,0.9647379,0.0001537481,0.00007920564,0.000133551,0.003063884,0.002859386,0.0003808335,0.004352781,0.0241279,0.00006735392],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8759294,0.008100048,0.002515579,0.006461045,0.00005834913,0.0001039319,0.06990951,0.0001690976,0.0367529],"genre_scores_gemma":[0.9706448,0.003590877,0.001447217,0.0003684276,0.00004507859,0.00002196293,0.02040883,0.00003290628,0.003439857],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01584148,"threshold_uncertainty_score":0.07723451,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08891987112154986,"score_gpt":0.2761275986545642,"score_spread":0.1872077275330143,"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."}}