{"id":"W2143227588","doi":"10.1016/j.respol.2014.11.007","title":"How does information technology improve aggregate productivity? A new channel of productivity dispersion and reallocation","year":2014,"lang":"en","type":"article","venue":"Research Policy","topic":"Economic Growth and Productivity","field":"Economics, Econometrics and Finance","cited_by":60,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"National Research Foundation of Korea; Ewha Womans University; Korea University; Sogang University; Seoul National University; Institute of Management Research, College of Business Administration Seoul National University","keywords":"Productivity; Economics; Industrial organization; Aggregate (composite); Production (economics); Productivity model; Channel (broadcasting); Dispersion (optics); Total factor productivity; Microeconomics; Macroeconomics; Telecommunications; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002719837,0.0001402745,0.0003462868,0.001357088,0.0001629886,0.0001178426,0.0002358565,0.0001479744,0.000005396534],"category_scores_gemma":[0.005810173,0.0001325434,0.00004289228,0.0008310071,0.0003196342,0.001573452,0.0002156259,0.0003273869,0.00004592238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001529428,"about_ca_system_score_gemma":0.0001463855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003237271,"about_ca_topic_score_gemma":0.0001027772,"domain_scores_codex":[0.9985337,0.0000759131,0.0003413649,0.0004951956,0.00007974551,0.0004741299],"domain_scores_gemma":[0.9986168,0.00006622414,0.0003416796,0.0006459511,0.0001822896,0.0001470465],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001087116,0.0001473871,0.02678253,0.0005606025,0.00005049439,1.858491e-7,0.001551733,0.000009713013,0.006031508,0.7435437,0.0007974648,0.2204159],"study_design_scores_gemma":[0.0009828641,0.0005340233,0.03426876,0.00004879248,0.000004473797,0.000008193369,0.0002060243,0.001864663,0.04670354,0.8307106,0.08427255,0.0003954469],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9084086,0.0003814286,0.002808052,0.0838528,0.0002191822,0.0008299022,0.00006945647,0.00005795501,0.003372566],"genre_scores_gemma":[0.9971837,0.0001913756,0.0003200208,0.00002909892,0.0006708142,0.00004336537,0.0000105259,0.00001416167,0.001536913],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2200205,"threshold_uncertainty_score":0.6955739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03744842534750239,"score_gpt":0.2799894101475565,"score_spread":0.2425409848000541,"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."}}