{"id":"W4224307008","doi":"10.1017/s000305542200020x","title":"Intrinsic Social Incentives in State and Non-State Armed Groups","year":2022,"lang":"en","type":"article","venue":"American Political Science Review","topic":"Defense, Military, and Policy Studies","field":"Economics, Econometrics and Finance","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Folke Bernadotteakademin; Sveriges Regering; University of Cambridge; York University; London School of Economics and Political Science; University of Pittsburgh","keywords":"Group cohesiveness; Incentive; Cohesion (chemistry); State (computer science); Social psychology; Political science; Psychology; Public economics; Public relations; Economics; Business; Microeconomics; Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001379238,0.0001387754,0.0006068686,0.0002082992,0.0003751943,0.00003135479,0.0002989683,0.00000681287,0.0001001848],"category_scores_gemma":[0.0003337567,0.0001435573,0.00007220433,0.001426291,0.002056916,0.0001626586,0.0003857079,0.0001953945,0.0001013095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003232938,"about_ca_system_score_gemma":0.00008122589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003786998,"about_ca_topic_score_gemma":0.00009098915,"domain_scores_codex":[0.9979229,0.00006030668,0.0005109755,0.0004708632,0.0001038526,0.0009311217],"domain_scores_gemma":[0.9993298,0.00009985245,0.0001652171,0.0001646756,0.0000233597,0.0002170921],"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":[0.00001783898,0.000202241,0.1106176,0.0005288508,0.00002970417,0.00002225084,0.003475962,0.00000157353,0.000004998889,0.785799,0.001672724,0.09762722],"study_design_scores_gemma":[0.0003528993,0.0002278844,0.7959206,0.00009725369,0.000009454962,0.00001044292,0.0009968296,0.00006766699,0.000003236928,0.1092547,0.09257912,0.0004799877],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9254138,0.03288809,0.0000312014,0.01710142,0.0001963732,0.000479847,0.0002546831,0.00002095366,0.02361356],"genre_scores_gemma":[0.9740329,0.01920399,0.0000565821,0.006452722,0.00003557893,0.00006777626,0.000001733179,0.0000084142,0.0001402959],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6853029,"threshold_uncertainty_score":0.7578791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02551968664762183,"score_gpt":0.2833856985152755,"score_spread":0.2578660118676536,"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."}}