{"id":"W6887857865","doi":"10.17632/vkyy9yp579.1","title":"The Social Costs of Political Divide: Evidence from the Impact of Polarization Risk on CSR","year":2025,"lang":"en","type":"dataset","venue":"Mendeley Data","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Dalhousie University","funders":"","keywords":"Polarization (electrochemistry); Politics; Social risk; Corporate social responsibility; Political risk; Economic impact analysis","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00203332,0.0006265335,0.0005751613,0.002646562,0.0008505588,0.002220394,0.001885545,0.001397073,0.01767219],"category_scores_gemma":[0.01094137,0.000306515,0.0006992422,0.00544344,0.0005103817,0.001682426,0.001885199,0.001757763,0.009727001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002705246,"about_ca_system_score_gemma":0.001397099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1202087,"about_ca_topic_score_gemma":0.1715028,"domain_scores_codex":[0.9985411,0.0004094826,0.0001530851,0.000197004,0.0005494446,0.0001499162],"domain_scores_gemma":[0.9926998,0.001953473,0.001958229,0.0009912053,0.001942617,0.0004545864],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001694247,0.00008842512,0.01874474,0.0004852356,0.00008617181,0.00003768228,0.0001498136,0.0006175651,0.00005892546,0.005203614,0.9680412,0.006317151],"study_design_scores_gemma":[0.0004715081,0.00004985699,0.1669776,0.0008013894,0.0001075456,0.0001218005,0.001511213,0.001820156,0.0006844881,0.004329299,0.8230267,0.00009839841],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.008301863,0.0008425725,0.0002174192,0.002046949,0.00009981897,0.00003973119,0.9788076,0.0001001629,0.009543966],"genre_scores_gemma":[0.03481686,0.0006499366,0.0008959486,0.0004864547,0.00006211946,0.0001827847,0.9568528,0.00006741608,0.00598563],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1202087,"threshold_uncertainty_score":0.239018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08176113122093259,"score_gpt":0.4114823381769441,"score_spread":0.3297212069560115,"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."}}