{"id":"W7113075013","doi":"","title":"Risk and the Gender Gap in Attitudes toward Artificial Intelligence","year":2025,"lang":"","type":"preprint","venue":"OSF Preprints (OSF Preprints)","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Skepticism; Gender gap; Government (linguistics); Intervention (counseling); Work (physics); Risk aversion (psychology); Economic interventionism","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.003540267,0.000124262,0.0002281431,0.001054855,0.001090773,0.001800851,0.000257692,0.0005410665,0.007370611],"category_scores_gemma":[0.01174374,0.000154166,0.0001912069,0.0008679574,0.001837935,0.001416983,0.001369063,0.0008620778,0.0005411737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007583863,"about_ca_system_score_gemma":0.0007981445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0125153,"about_ca_topic_score_gemma":0.01560737,"domain_scores_codex":[0.9984012,0.0006082951,0.00005751626,0.0002028205,0.0003886528,0.000341564],"domain_scores_gemma":[0.9904531,0.005096412,0.00220879,0.0002886463,0.0008444421,0.001108669],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002635565,0.0001999331,0.8563157,0.00007570028,0.00006986637,0.0002673271,0.07510352,0.0001499593,0.0007443897,0.02007782,0.00230253,0.04442982],"study_design_scores_gemma":[0.00001690669,0.0001298791,0.894236,0.0001617351,0.00002302386,0.0002269829,0.0842512,0.0003569836,0.0002779419,0.008586994,0.01170666,0.0000257134],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9838367,0.0007737713,0.000336916,0.002867872,0.00003895216,0.000007204409,0.0001096283,0.000001974695,0.01202703],"genre_scores_gemma":[0.9986367,0.0002351849,0.00004616998,0.0002726445,0.00001355199,0.00000451096,0.00003072046,0.000002390191,0.0007580619],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0125153,"threshold_uncertainty_score":0.02488494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09268667846749482,"score_gpt":0.3751980307349977,"score_spread":0.2825113522675029,"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."}}