{"id":"W4406480489","doi":"10.1111/jori.12503","title":"A fair price to pay: Exploiting causal graphs for fairness in insurance","year":2025,"lang":"en","type":"article","venue":"Journal of Risk & Insurance","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; Université Laval","funders":"","keywords":"Actuarial science; Economics; Business","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":[0.03813666,0.0007674902,0.001011495,0.00339026,0.001956639,0.004642157,0.002004666,0.002537463,0.004348125],"category_scores_gemma":[0.1317828,0.0005386452,0.001254297,0.002273545,0.008581229,0.008948664,0.003811207,0.004048185,0.0002766568],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00343643,"about_ca_system_score_gemma":0.002679134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002109097,"about_ca_topic_score_gemma":0.00177622,"domain_scores_codex":[0.9760543,0.01703209,0.0006612512,0.002472506,0.003228495,0.0005513694],"domain_scores_gemma":[0.8490025,0.1249071,0.007473965,0.01293967,0.00412458,0.001552107],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003407668,0.00003163521,0.001741368,0.00004296373,0.00003071993,0.00004522382,0.0002991164,0.0266053,0.0002393104,0.9465052,0.0006280013,0.02379707],"study_design_scores_gemma":[0.000007806106,0.00001602884,0.0003139685,0.00002798781,0.00001200839,0.00002313007,0.00004651182,0.07432318,0.0002472033,0.9238443,0.001126453,0.00001137255],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01696711,0.0001597087,0.9772953,0.00188853,0.0000469828,0.00007086361,0.00006333657,0.0001151104,0.003393149],"genre_scores_gemma":[0.7287503,0.0002301717,0.2687983,0.0005656165,0.0001699054,0.000179906,0.00006598078,0.00009025628,0.001149547],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03813666,"threshold_uncertainty_score":0.2016883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02616377803767753,"score_gpt":0.3645533110817164,"score_spread":0.3383895330440388,"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."}}