{"id":"W3044606135","doi":"10.1002/pan3.10124","title":"Levers and leverage points for pathways to sustainability","year":2020,"lang":"en","type":"article","venue":"People and Nature","topic":"Sustainability and Climate Change Governance","field":"Environmental Science","cited_by":313,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre; Fisheries and Oceans Canada; McGill University; Western Forest Products; University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada; Environment and Climate Change Canada; Natural Sciences and Engineering Research Council of Canada; University of British Columbia; AgBioResearch, Michigan State University; National Science Foundation","keywords":"Sustainability; Deliberation; Business; Incentive; Leverage (statistics); Environmental economics; Economics; Environmental resource management; Public economics; Political science; Computer science; Microeconomics; Ecology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03433207,0.001016024,0.0007792283,0.005409952,0.003818076,0.01233271,0.002006159,0.00422337,0.01023899],"category_scores_gemma":[0.0459825,0.0006839777,0.001341088,0.003235505,0.02067046,0.0126667,0.01615287,0.005693525,0.0006035089],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009986186,"about_ca_system_score_gemma":0.01269889,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001758231,"about_ca_topic_score_gemma":0.002679767,"domain_scores_codex":[0.959959,0.02637135,0.002034446,0.003080606,0.005403128,0.003151505],"domain_scores_gemma":[0.9641609,0.02451723,0.003100128,0.002355338,0.004001108,0.001865311],"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":[0.00005248696,0.00009000385,0.003091221,0.0009863458,0.00005844466,0.0004326861,0.007840386,0.006199487,0.001148389,0.9391216,0.001913994,0.03906495],"study_design_scores_gemma":[0.00002621568,0.0001350669,0.002418159,0.001341397,0.00006369635,0.0001239842,0.009978793,0.004221635,0.001186377,0.9363,0.04413797,0.00006664265],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1372311,0.005773518,0.5007476,0.05931108,0.000571728,0.003236168,0.0004212549,0.0006802873,0.2920272],"genre_scores_gemma":[0.9339349,0.001133499,0.06050155,0.001040807,0.00004084415,0.001041179,0.00008306793,0.00004167432,0.00218248],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03433207,"threshold_uncertainty_score":0.1815675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01242906584011651,"score_gpt":0.2343169582774433,"score_spread":0.2218878924373268,"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."}}