{"id":"W2322115106","doi":"10.5751/es-06656-190273","title":"Resource degradation, marginalization, and poverty in small-scale fisheries: threats to social-ecological resilience in India and Brazil","year":2014,"lang":"en","type":"article","venue":"Ecology and Society","topic":"Innovation and Socioeconomic Development","field":"Business, Management and Accounting","cited_by":158,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; University of Waterloo","funders":"Social Sciences and Humanities Research Council of Canada; Conselho Nacional de Desenvolvimento Científico e Tecnológico; University of Waterloo; International Development Research Centre; Canada Excellence Research Chairs, Government of Canada; Canada Research Chairs","keywords":"Poverty; Environmental degradation; Ecological resilience; Resilience (materials science); Scale (ratio); Resource (disambiguation); Psychological resilience; Fishery; Geography; Environmental resource management; Ecology; Economics; Economic growth; Ecosystem; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.001055399,0.000184362,0.0002725597,0.001775938,0.001868696,0.001580411,0.0006021544,0.0004714711,0.001760068],"category_scores_gemma":[0.003660611,0.0001899297,0.0003718304,0.002007403,0.003381849,0.00131546,0.00364045,0.0006518287,0.00005744848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003022037,"about_ca_system_score_gemma":0.003219718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1380359,"about_ca_topic_score_gemma":0.2251629,"domain_scores_codex":[0.9993061,0.0001939592,0.00005196344,0.00005392635,0.0001157002,0.0002783965],"domain_scores_gemma":[0.9979493,0.0005491878,0.000693742,0.000106449,0.000250067,0.0004512937],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001344995,0.0001271309,0.8655035,0.0003376703,0.0001541051,0.00249235,0.06483467,0.0008791729,0.001006848,0.0185386,0.001728292,0.04426313],"study_design_scores_gemma":[0.000007778236,0.00008046874,0.879699,0.0004321951,0.00009720417,0.001037399,0.1049356,0.001350164,0.0003977264,0.005856203,0.006062057,0.0000442388],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9929885,0.001300042,0.00008969781,0.002293861,0.000005742656,0.00001176227,0.00008801678,0.000003159718,0.003219162],"genre_scores_gemma":[0.999486,0.0003954858,0.00002189135,0.00002867365,0.000001242278,0.000002448452,0.00001150372,5.856943e-7,0.00005227318],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1380359,"threshold_uncertainty_score":0.2744649,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0100880560283718,"score_gpt":0.2183103586814323,"score_spread":0.2082223026530605,"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."}}