{"id":"W2573959285","doi":"10.1287/mnsc.2016.2619","title":"Industrial Development Through Tacit Knowledge Seeding: Evidence from the Bangladesh Garment Industry","year":2017,"lang":"en","type":"article","venue":"Management Science","topic":"Firm Innovation and Growth","field":"Economics, Econometrics and Finance","cited_by":93,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Tacit knowledge; Industrialisation; Business; Industrial organization; Empirical evidence; Developing country; Marketing; Knowledge management; Economics; Economic growth; Market economy; 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":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001923503,0.0001658946,0.0001876827,0.0001369725,0.001660835,0.001031543,0.002168012,0.0001079934,0.0004768214],"category_scores_gemma":[0.0003280599,0.0001452599,0.0000416151,0.0005553268,0.0004736463,0.001236753,0.000987566,0.0003351556,0.0009881957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002613705,"about_ca_system_score_gemma":0.00006015323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001877596,"about_ca_topic_score_gemma":0.0000199049,"domain_scores_codex":[0.9982325,0.000009987044,0.0004981267,0.0006656143,0.0001779594,0.0004158173],"domain_scores_gemma":[0.9984532,0.00004865071,0.0004584408,0.0009209152,0.00004828277,0.00007049027],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001366255,0.0001543104,0.522908,0.00001931388,0.00006871745,0.000008519614,0.00375325,0.00002179788,0.00004511403,0.4279815,0.02862716,0.01639864],"study_design_scores_gemma":[0.0005434461,0.00002120072,0.5985796,0.0001356416,0.000006294085,5.086683e-7,0.0004015572,0.0003732808,0.000661604,0.007440883,0.3915322,0.0003037927],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6569701,0.0005225934,0.004353577,0.01121325,0.003891537,0.0008049454,0.00002753011,0.0000871591,0.3221292],"genre_scores_gemma":[0.9912595,0.00004467072,0.001811891,0.0007327016,0.0002641935,0.000051683,0.000003396388,0.00001006231,0.005821889],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4205406,"threshold_uncertainty_score":0.9997897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2213470362130286,"score_gpt":0.3062235318449383,"score_spread":0.08487649563190966,"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."}}