{"id":"W2508612197","doi":"10.17645/pag.v4i3.564","title":"Contested Norms in Inter-National Encounters: The ‘Turbot War’ as a Prelude to Fairer Fisheries Governance","year":2016,"lang":"en","type":"article","venue":"Politics and Governance","topic":"International Maritime Law Issues","field":"Environmental Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institute for Advanced Studies in the Humanities, University of Edinburgh; Universität Hamburg; University of Edinburgh; University of St Andrews; Volkswagen Foundation; University of Victoria","keywords":"Corporate governance; Political science; Politics; Norm (philosophy); Fisheries law; Fisheries management; Stakeholder; Section (typography); Global governance; Citizen journalism; Fishery; Public relations; Law; Business; Management; Economics; Fishing","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001386903,0.000138901,0.0001158393,0.000007418257,0.00006447118,0.00004528612,0.0003228233,0.00004040644,0.0008543686],"category_scores_gemma":[0.0004281432,0.00008500224,0.00003006325,0.00008171094,0.0002467387,0.0003331308,0.0002534789,0.00008121979,0.0003229319],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004244499,"about_ca_system_score_gemma":0.00002087306,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008520919,"about_ca_topic_score_gemma":0.004521248,"domain_scores_codex":[0.9987208,0.00002300812,0.0002149962,0.0002769252,0.0004713775,0.0002928794],"domain_scores_gemma":[0.999477,0.000168681,0.00009345172,0.000159642,0.00002637472,0.0000748536],"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":[0.0001243946,0.0001897614,0.4625359,0.00002241034,0.00003700603,0.00003598457,0.003028139,0.00006898001,0.003369819,0.4677857,0.05399891,0.008802961],"study_design_scores_gemma":[0.0003793686,0.00007262335,0.7856316,0.0001384648,0.000002627074,0.00001849935,0.00003648268,0.0001468276,0.0010741,0.01735884,0.1949571,0.0001835022],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9072792,0.0001031014,0.0001235586,0.03322133,0.0002614901,0.0002439843,0.0002089317,0.00002199682,0.05853641],"genre_scores_gemma":[0.9777892,0.00009637201,0.0001514276,0.002925518,0.0000714808,0.00004184171,0.000001255601,0.00001227078,0.01891067],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4504269,"threshold_uncertainty_score":0.9980814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006982545278743118,"score_gpt":0.224701242009884,"score_spread":0.2177186967311409,"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."}}