{"id":"W2187599475","doi":"10.5281/zenodo.6385159","title":"Gender Justice and Climate Justice: Community-Based Strategies to Increase Women's Political Agency in Watershed Management in Times of Climate Change","year":2011,"lang":"en","type":"article","venue":"York University Digital Library (York University)","topic":"Environmental Education and Sustainability","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agency (philosophy); Politics; Climate change; Economic Justice; Watershed; Climate justice; Environmental justice; Political science; Environmental resource management; Sociology; Environmental science; Social science; Ecology; Law","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001418131,0.0002095472,0.0002180891,0.0004114221,0.0002080243,0.00004910217,0.00049314,0.00008931701,0.001011569],"category_scores_gemma":[0.000007794402,0.0002519912,0.00005005123,0.00082298,0.0004330431,0.00200889,0.001045449,0.0002186777,0.00005694704],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004879384,"about_ca_system_score_gemma":0.00003356007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004557215,"about_ca_topic_score_gemma":0.00005749136,"domain_scores_codex":[0.9984273,0.0002706993,0.0001743312,0.0003495309,0.0001678556,0.0006103342],"domain_scores_gemma":[0.9991574,0.00008211713,0.00006469379,0.0003260801,0.00000403267,0.0003656448],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002241582,0.003219328,0.7967135,0.00147249,0.00004700984,0.0008442458,0.02995822,0.0003645291,0.00002469425,0.1619564,0.0002675069,0.00289047],"study_design_scores_gemma":[0.001587638,0.0002492116,0.6374746,0.00005779642,0.0001217054,0.000002526366,0.3499972,0.0001152016,0.00004102421,0.001788978,0.008036755,0.0005273711],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.724083,0.000003146087,0.00002011189,0.00009290488,0.00002159791,0.0003007446,0.0001090238,0.00004327319,0.2753262],"genre_scores_gemma":[0.9977887,0.0000500709,0.0009889614,0.000323807,0.000004883319,9.393515e-7,0.00006454009,0.00001341096,0.0007646658],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.320039,"threshold_uncertainty_score":0.9999932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02321172793167504,"score_gpt":0.2059135305045086,"score_spread":0.1827018025728336,"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."}}