{"id":"W4380875813","doi":"10.1002/9781119511847.ch16","title":"Rights‐Based Approaches to Fisheries Management","year":2023,"lang":"en","type":"other","venue":"","topic":"International Maritime Law Issues","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint Mary's University","funders":"","keywords":"Human rights; Fisheries law; Fishing; Fisheries management; Fishery; Perspective (graphical); Fish <Actinopterygii>; Theme (computing); Political science; Transferability; Relevance (law); Business; Environmental resource management; Law and economics; Law; Economics; Economic growth; Computer science; Human capital","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006207661,0.001374795,0.0006722205,0.003019541,0.004278918,0.009074784,0.00309505,0.004520747,0.0154797],"category_scores_gemma":[0.004285751,0.0004511412,0.0009242627,0.003119427,0.0276737,0.0100749,0.004903332,0.006461435,0.002339329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01034578,"about_ca_system_score_gemma":0.007460502,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009703041,"about_ca_topic_score_gemma":0.01123291,"domain_scores_codex":[0.994516,0.002572781,0.0002865811,0.0006504286,0.001485762,0.0004885056],"domain_scores_gemma":[0.9980842,0.001052809,0.0001914599,0.000238588,0.0002805289,0.0001523991],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[5.462044e-7,0.000002937833,0.00001662841,0.00001234875,0.000001444848,0.000009065297,0.000132696,0.0002972741,0.000009390626,0.9959727,0.001188675,0.002356351],"study_design_scores_gemma":[0.000002537403,0.000004569752,0.00004889053,0.0001103444,0.000001895563,0.00001632188,0.0002609083,0.0004049524,0.00003075901,0.9138538,0.08526009,0.000004909421],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.001506908,0.01340302,0.09727477,0.03947722,0.0009382157,0.0001147251,0.0001088598,0.00006538808,0.8471109],"genre_scores_gemma":[0.4799562,0.05991148,0.1112469,0.01544681,0.0050543,0.001407445,0.0003024354,0.0002525976,0.326422],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0154797,"threshold_uncertainty_score":0.07506418,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04375816754807135,"score_gpt":0.2192199619337522,"score_spread":0.1754617943856808,"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."}}