{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004311768,0.0001666644,0.0003813208,0.001156453,0.001002035,0.002356321,0.0004059446,0.0009447141,0.006658705],"category_scores_gemma":[0.01493525,0.0002349892,0.0002256686,0.0007758766,0.002234349,0.001686948,0.001851276,0.0005581774,0.0003260681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001601155,"about_ca_system_score_gemma":0.0008883808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002334071,"about_ca_topic_score_gemma":0.004583711,"domain_scores_codex":[0.9976718,0.001343375,0.00008712508,0.0002085596,0.0002494368,0.000439749],"domain_scores_gemma":[0.9871877,0.006047733,0.004103739,0.0005736246,0.000614571,0.001472662],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003739861,0.0006930282,0.4717666,0.0002765987,0.000286954,0.0004919829,0.006083135,0.008921315,0.001527915,0.4451564,0.00316852,0.06125354],"study_design_scores_gemma":[0.00009669858,0.0003186226,0.7695205,0.0001860587,0.00008842169,0.0002643919,0.008010988,0.01509447,0.0004239799,0.1896942,0.01623756,0.00006420869],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9528675,0.000488796,0.003473717,0.001862778,0.00002762626,0.00004712682,0.0001427461,0.000009362314,0.04108045],"genre_scores_gemma":[0.9985671,0.0001049887,0.0002399219,0.00006586166,0.00001167674,0.00001477743,0.00002464584,0.00000142532,0.000969563],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006658705,"threshold_uncertainty_score":0.02280307,"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."}}