{"id":"W4400320374","doi":"10.1007/s44282-024-00064-6","title":"Intra-migrant workplace conflict: impediment to improving migrants’ workforce integration","year":2024,"lang":"en","type":"article","venue":"Discover Global Society","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Crandall University","funders":"","keywords":"Workforce; Migrant workers; Business; Political science; Demographic economics; Economic growth; Economics","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":[0.0006077203,0.0002033747,0.0001706899,0.00002010239,0.0004120264,0.0007145104,0.0002616574,0.0001732337,0.0001899642],"category_scores_gemma":[0.00008787844,0.0001756328,0.0002830088,0.000984585,0.0001375544,0.0004251661,0.00006253975,0.000203191,0.0001394764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007734974,"about_ca_system_score_gemma":0.0003645561,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004659567,"about_ca_topic_score_gemma":0.02062325,"domain_scores_codex":[0.9981644,0.00008389405,0.0002775266,0.0004233969,0.0005638335,0.0004869237],"domain_scores_gemma":[0.9993544,0.00006745514,0.00004946117,0.0001900828,0.00008521783,0.0002534454],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005355634,0.0001097814,0.002370544,0.00006192383,0.0001371851,0.000009584242,0.2929321,0.0005912461,0.001057662,0.409784,0.172127,0.1207655],"study_design_scores_gemma":[0.000288948,0.00006183729,0.000985498,0.0002701821,0.00007367579,0.000001745409,0.05427687,0.02150489,0.00009558714,0.001068874,0.9208351,0.0005367768],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7778409,0.003941497,0.1588828,0.02134009,0.003922534,0.001686695,0.00047383,0.0009604042,0.03095126],"genre_scores_gemma":[0.9873174,0.0004735104,0.001341388,0.003058461,0.000527402,0.00004735116,0.0000600222,0.0000182319,0.007156218],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7487081,"threshold_uncertainty_score":0.9972478,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01412275166967132,"score_gpt":0.3096818625882155,"score_spread":0.2955591109185441,"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."}}