{"id":"W1975155767","doi":"10.1093/icc/dtr029","title":"Information technology and the changing workplace in Canada: firm-level evidence","year":2011,"lang":"en","type":"article","venue":"Industrial and Corporate Change","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; University of Saskatchewan","funders":"Social Sciences and Humanities Research Council of Canada; University of Saskatchewan","keywords":"Productivity; Spillover effect; Information and Communications Technology; Information technology; The Internet; Business; Human capital; Competition (biology); Sample (material); Industrial organization; Marketing; Technological change; Labour economics; Momentum (technical analysis); Control (management); Economics; Microeconomics; Management; Market economy; Economic growth","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009097844,0.0000989057,0.0002335045,0.0002530913,0.00007637197,0.00003643529,0.0001215759,0.0001141458,0.000032713],"category_scores_gemma":[0.0001754337,0.00008150636,0.00001273881,0.0006173751,0.00008469306,0.000387797,0.0001116961,0.0001973247,0.000004780803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001035066,"about_ca_system_score_gemma":0.00007524952,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.4809087,"about_ca_topic_score_gemma":0.2395993,"domain_scores_codex":[0.9992537,0.00002357383,0.0003563116,0.0001295813,0.00002848098,0.0002082866],"domain_scores_gemma":[0.9993638,0.0000641088,0.00037228,0.0001360511,0.00002380137,0.00003993935],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002106354,0.000008943654,0.5852794,0.00001801001,0.0000146978,0.000007285234,0.002882528,6.539042e-7,3.202354e-7,0.3841498,0.00006285425,0.02736486],"study_design_scores_gemma":[0.007864228,0.0001515492,0.4645523,0.0004001819,0.0000228242,0.00002803343,0.006551988,0.006071675,0.0000360631,0.5032123,0.01012625,0.0009826269],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942559,0.001447727,0.0001095645,0.002739632,0.0003603248,0.0003245549,0.0001103596,0.00001018889,0.0006417517],"genre_scores_gemma":[0.9987926,0.0005654737,0.00002767206,0.0003974698,0.00007263861,0.00006355389,0.000005014969,0.000004561779,0.00007097888],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2413094,"threshold_uncertainty_score":0.774276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2598018880091842,"score_gpt":0.2173525174493,"score_spread":0.04244937055988426,"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."}}