{"id":"W4385785982","doi":"10.1108/ijopm-09-2022-0596","title":"Reducing forced labour in supply chains: what could traditional companies learn from social enterprises?","year":2023,"lang":"en","type":"article","venue":"International Journal of Operations & Production Management","topic":"Global trade, sustainability, and social impact","field":"Business, Management and Accounting","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Supply chain; Originality; Business; Generalizability theory; Industrial organization; Marketing; Economics; Sociology; Qualitative research","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0007387426,0.0001748148,0.0002290668,0.0008637538,0.0003049531,0.001196202,0.0004215932,0.00005682983,0.0002106842],"category_scores_gemma":[0.0001998801,0.0001781668,0.0001584569,0.0006681299,0.00007836856,0.00413504,0.0001194064,0.0002461843,0.00006051569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003948863,"about_ca_system_score_gemma":0.00005344561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005693331,"about_ca_topic_score_gemma":0.000164585,"domain_scores_codex":[0.9979333,0.00004728565,0.0006768106,0.0002755994,0.0008215252,0.0002454329],"domain_scores_gemma":[0.9987759,0.00002617781,0.0002672594,0.0001157045,0.000794343,0.00002062797],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.001323585,0.003321388,0.03889921,0.0004182742,0.002746968,0.0007726768,0.02474333,0.4236386,0.001689264,0.3526976,0.07151524,0.07823385],"study_design_scores_gemma":[0.004702699,0.00009682751,0.7064717,0.0008275296,0.0003114472,0.00003357615,0.1608366,0.01466593,0.0001374095,0.05132855,0.05961557,0.0009721261],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9597744,0.00009063,0.0003891518,0.03327838,0.005055828,0.000363499,0.00002304267,0.00007196453,0.0009530385],"genre_scores_gemma":[0.9923002,0.0003320959,0.0002203865,0.0008758669,0.005231977,0.00002043426,0.0002176569,0.00001986895,0.0007815436],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6675726,"threshold_uncertainty_score":0.9998407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04085843913633586,"score_gpt":0.2975351925655778,"score_spread":0.256676753429242,"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."}}