{"id":"W1977747521","doi":"10.5539/ijef.v2n4p113","title":"Impact of Enforcement and Co-Management on Compliance Behavior of Fishermen","year":2010,"lang":"en","type":"article","venue":"International Journal of Economics and Finance","topic":"Cybercrime and Law Enforcement Studies","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Economy and Environment Program for Southeast Asia","keywords":"Compliance (psychology); Enforcement; Deterrence theory; Business; Public economics; Legitimacy; Empirical research; Deterrence (psychology); Law enforcement; Economics; Law and economics; Psychology; Political science; Social psychology; Law","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0001273383,0.00006226423,0.0001429166,0.00007175042,0.00002026409,0.00002576036,0.0002879173,0.00001538105,0.00001099727],"category_scores_gemma":[0.000004116701,0.00005281973,0.00005715089,0.00001662922,0.00005514813,0.0001779527,0.00009333767,0.00006338252,5.017922e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002036883,"about_ca_system_score_gemma":0.00001701731,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003739357,"about_ca_topic_score_gemma":0.000008131421,"domain_scores_codex":[0.9994764,0.000003100397,0.0003112628,0.00008132607,0.00006714519,0.00006082037],"domain_scores_gemma":[0.9994408,0.00002560299,0.0003286802,0.00009130195,0.00009504313,0.00001856525],"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":[0.0001301459,0.0002827186,0.02713618,0.00001614464,0.0003994614,0.00001553216,0.0005155127,0.002019615,0.0006339342,0.8090695,0.0005704388,0.1592108],"study_design_scores_gemma":[0.003110106,0.001569049,0.9440172,0.0001936479,0.00004005062,0.0001054796,0.00004833042,0.01298181,0.004959728,0.007306145,0.02537129,0.0002971152],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9947432,0.00004896825,0.0003652326,0.0001067909,0.0002691432,0.00004839088,0.00001160695,8.09391e-7,0.00440588],"genre_scores_gemma":[0.9963654,0.001788515,0.001701453,0.00004101236,0.00003078218,0.00000155816,5.922456e-7,0.000002012255,0.00006864662],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9168811,"threshold_uncertainty_score":0.2153926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02449653029055257,"score_gpt":0.2991108368707014,"score_spread":0.2746143065801488,"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."}}