{"id":"W7126593479","doi":"","title":"RELATIONSHIP-BASED LENDING FOR DIVERSIFIED AGRICULTURE SYSTEMS IN CANADA: HOW TRUST AND COMMUNITY MAY TRANSFORM FINANCIALIZED AND GENDERED FOOD SYSTEMS","year":2021,"lang":"en","type":"other","venue":"eCommons (Cornell University)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agriculture; Incentive; Food systems; Snowball sampling; Food security; Work (physics); Multinational corporation; Asset (computer security); Agribusiness","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001921897,0.0002648167,0.0003384016,0.001122837,0.02443001,0.006112249,0.001351327,0.0007298124,0.004203775],"category_scores_gemma":[0.004240731,0.0002568085,0.0002116489,0.002010264,0.009828413,0.001962075,0.005395629,0.001803666,0.0001537232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1046153,"about_ca_system_score_gemma":0.1495215,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9906735,"about_ca_topic_score_gemma":0.9972134,"domain_scores_codex":[0.9981729,0.0003755818,0.00003622369,0.000150641,0.00032488,0.000939824],"domain_scores_gemma":[0.9964873,0.0006170396,0.0003134795,0.0001239089,0.0008270841,0.001631221],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001377028,0.0001135721,0.126365,0.0001861749,0.00002272918,0.002569795,0.7592974,0.0004783993,0.001513433,0.03899753,0.008278622,0.06203964],"study_design_scores_gemma":[0.00001248406,0.0000454571,0.1006576,0.0002201864,0.00002094005,0.0002168058,0.8273829,0.0006432204,0.0004224764,0.002906695,0.06741749,0.00005375797],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9604074,0.0007827992,0.0005420107,0.008610997,0.00004037513,0.00006604862,0.0001917883,0.00001890043,0.0293397],"genre_scores_gemma":[0.9938974,0.0004414194,0.0003404257,0.000322623,0.000003295813,0.00001249363,0.00003226509,0.000007157021,0.004942894],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1046153,"threshold_uncertainty_score":0.7590407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07072478350322359,"score_gpt":0.1953092606609733,"score_spread":0.1245844771577497,"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."}}