{"id":"W2766159367","doi":"10.5465/ambpp.2017.15934abstract","title":"Resourcing for Inclusion of Marginalized Actors in Transnational Governance","year":2017,"lang":"en","type":"article","venue":"Academy of Management Proceedings","topic":"International Maritime Law Issues","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Disadvantaged; Context (archaeology); Inclusion (mineral); Corporate governance; Public relations; Negotiation; Sociology; Political science; Institution; Indigenous; Business; Social science; Law","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":[0.0005117537,0.00008529917,0.0001380066,0.00003995596,0.0001445377,0.00001515986,0.0006723796,0.00005491073,0.0002561905],"category_scores_gemma":[0.00005768384,0.00008769563,0.00004708305,0.00005629807,0.0001347597,0.0004894605,0.0007302643,0.00007177686,0.000002562008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000970673,"about_ca_system_score_gemma":0.00000121429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005882069,"about_ca_topic_score_gemma":0.000004668198,"domain_scores_codex":[0.9989008,0.00000312356,0.0002678161,0.0002088335,0.00047773,0.0001416977],"domain_scores_gemma":[0.9995418,0.00002998464,0.0003463493,0.00004976843,0.00001195608,0.00002015723],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0003001737,0.0001312113,0.09273089,0.0003884035,0.00003825101,7.532206e-7,0.0009162899,0.0001016649,0.01507949,0.8757244,0.001726298,0.0128622],"study_design_scores_gemma":[0.001226173,0.00003294889,0.8831577,0.0001417737,0.00001879149,4.411681e-7,0.00004801031,0.001120842,0.0218447,0.03757918,0.05469626,0.0001331275],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9242725,0.00001546044,0.00008511857,0.007072465,0.0000238403,0.0004320341,0.000007634997,0.000008820098,0.06808208],"genre_scores_gemma":[0.9924995,0.00002720519,0.005372712,0.0001031774,0.00001559645,0.00003466379,0.000001331282,0.000009125292,0.001936688],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8381452,"threshold_uncertainty_score":0.3576124,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01817920396458936,"score_gpt":0.2829927470218879,"score_spread":0.2648135430572985,"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."}}