{"id":"W3047612394","doi":"10.1016/j.marpol.2020.104150","title":"Empowering small-scale, community-based fisheries through a food systems framework","year":2020,"lang":"en","type":"article","venue":"Marine Policy","topic":"Indigenous Studies and Ecology","field":"Health Professions","cited_by":33,"is_retracted":false,"has_abstract":false,"ca_institutions":"Assembly of First Nations; Mount Saint Vincent University; Lakehead University; Wilfrid Laurier University; Queen's University","funders":"Social Sciences and Humanities Research Council of Canada; Federation for the Humanities and Social Sciences","keywords":"Sustainability; Nexus (standard); Corporate governance; Fishery; General partnership; Fisheries management; Context (archaeology); Business; Fisheries law; Scale (ratio); Food systems; Fisheries science; Food security; Environmental resource management; Fishing; Geography; Economics; Ecology; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0003531434,0.0002224425,0.0004808396,0.00005239879,0.004768729,0.0000210634,0.0003555131,0.0002810582,0.0003236961],"category_scores_gemma":[0.0005295202,0.000206471,0.00008536542,0.0003797123,0.00008708269,0.00004974759,0.001112383,0.001543888,0.0003335535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002485673,"about_ca_system_score_gemma":0.0004199287,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.07477938,"about_ca_topic_score_gemma":0.03474926,"domain_scores_codex":[0.9974242,0.0006527107,0.0004792188,0.0001983515,0.000109682,0.001135775],"domain_scores_gemma":[0.9983985,0.000693435,0.0001774968,0.0004431117,0.0001322343,0.0001552257],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002822978,0.0002545047,0.4631882,0.004137611,0.0002804376,0.00001824164,0.4670236,0.0002391231,0.00002311122,0.04047123,0.02340919,0.000672498],"study_design_scores_gemma":[0.001498867,0.001615862,0.0336915,0.0002081624,0.00005230587,0.00000340967,0.09115382,0.0003132963,0.0000164977,0.003481007,0.8673794,0.0005858352],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.673942,0.0001370023,0.003585839,0.07603634,0.001454482,0.001923356,0.0001081781,0.0006528404,0.24216],"genre_scores_gemma":[0.9567461,0.00004588512,0.001949013,0.03823589,0.001879411,0.0003729189,0.00005026997,0.00006292478,0.0006575704],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8439702,"threshold_uncertainty_score":0.996527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1187256982747061,"score_gpt":0.392187114503354,"score_spread":0.2734614162286479,"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."}}