{"id":"W2185712647","doi":"10.25071/1705-1436.137","title":"Can Joint Training Increase Union Knowledge and Power?","year":2005,"lang":"en","type":"article","venue":"Just Labour","topic":"Labor Movements and Unions","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Restructuring; Globalization; Leverage (statistics); Training (meteorology); Power (physics); Economic system; Business; Work (physics); Labour economics; Economics; Political science; Engineering; Market economy; Computer science; Finance; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007341717,0.0002189728,0.0003691639,0.001201048,0.003219955,0.005489287,0.001320276,0.003228317,0.0229033],"category_scores_gemma":[0.02356395,0.0002160751,0.0003259653,0.001334931,0.005230439,0.008226864,0.00624805,0.001560543,0.002343792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002185531,"about_ca_system_score_gemma":0.003879448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001978891,"about_ca_topic_score_gemma":0.004472603,"domain_scores_codex":[0.9940439,0.003337203,0.0001051962,0.00029151,0.0007383499,0.001483852],"domain_scores_gemma":[0.985921,0.006878332,0.001671163,0.0008522719,0.0009333892,0.003743829],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002438972,0.002622329,0.03653057,0.0006526656,0.00005001243,0.0003948994,0.02407766,0.001189058,0.0006045892,0.1750997,0.02459033,0.7339444],"study_design_scores_gemma":[0.0003575027,0.002223251,0.1266618,0.003917753,0.0001621142,0.0009977268,0.1564813,0.003462297,0.002431517,0.4117177,0.2914725,0.0001144919],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3465426,0.005997661,0.007579945,0.1176542,0.001215572,0.0001277329,0.00005883253,0.00009985272,0.5207237],"genre_scores_gemma":[0.9810547,0.002238561,0.001422046,0.002817534,0.0002959205,0.00005855652,0.00002454815,0.00001487663,0.01207331],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0229033,"threshold_uncertainty_score":0.07661915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0336459410776398,"score_gpt":0.304122566567702,"score_spread":0.2704766254900622,"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."}}