{"id":"W2565892155","doi":"10.1016/j.jenvman.2016.12.009","title":"Using nudges to reduce waste? The case of Toronto's plastic bag levy","year":2016,"lang":"en","type":"article","venue":"Journal of Environmental Management","topic":"Municipal Solid Waste Management","field":"Environmental Science","cited_by":170,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Nudge theory; Plastic bag; Demographics; Empirical evidence; Globe; Public economics; Discrete choice; Business; Economics; Marketing; Engineering; Psychology; Sociology; Econometrics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006745457,0.0002411286,0.0002768634,0.00005356211,0.0001375598,0.00002590702,0.0007015077,0.00003782892,0.0047432],"category_scores_gemma":[0.0000250816,0.0001409746,0.0001620568,0.00009825088,0.0002372686,0.0003758299,0.001249689,0.0000905629,0.0001319247],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001134429,"about_ca_system_score_gemma":0.000003331707,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000366673,"about_ca_topic_score_gemma":0.0001707141,"domain_scores_codex":[0.9978625,0.0001259232,0.0007150794,0.00028081,0.0006337207,0.0003819609],"domain_scores_gemma":[0.9986128,0.000114332,0.0004993567,0.0005674546,0.000003735388,0.0002023494],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009954356,0.002538895,0.00633155,0.0001826101,0.001403944,0.007669326,0.003199853,0.3457624,0.1862035,0.002288044,0.01852797,0.4248964],"study_design_scores_gemma":[0.02870578,0.0119036,0.2983625,0.003456638,0.006451094,0.01671514,0.1100842,0.02838825,0.08536128,0.0038277,0.3993609,0.007382844],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9869996,0.000192741,0.003500662,0.0005823926,0.0004686908,0.0005067451,0.00001379174,0.00000565957,0.007729703],"genre_scores_gemma":[0.9951915,0.0002108789,0.00305619,0.000191833,0.0001007545,0.000008148873,2.18273e-7,0.00002815314,0.001212396],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4175136,"threshold_uncertainty_score":0.9961666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02018583273663881,"score_gpt":0.2555849256709339,"score_spread":0.2353990929342951,"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."}}