{"id":"W4390061969","doi":"10.1086/727693","title":"Environmental and Natural Resource Economics and Systemic Racism","year":2023,"lang":"en","type":"article","venue":"Review of Environmental Economics and Policy","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Natural resource; Environmental justice; Racism; Commons; Sociology; Economics; Resource (disambiguation); Environmental studies; Work (physics); Natural resource management; Public economics; Environmental economics; Environmental resource management; Political science; Computer science; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006269259,0.000285483,0.0007061981,0.0002080537,0.0001269666,0.00003704802,0.000134539,0.0001181413,0.0001384117],"category_scores_gemma":[0.00001564373,0.0003424941,0.0001107048,0.00004274812,0.0003222639,0.0002894963,0.000310963,0.0001322755,0.0003105167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002291397,"about_ca_system_score_gemma":0.00001040499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004648225,"about_ca_topic_score_gemma":0.00000234244,"domain_scores_codex":[0.9981361,0.00002679362,0.0009157988,0.0005882033,0.0000229164,0.0003101726],"domain_scores_gemma":[0.9989293,0.0000667129,0.0005205119,0.000313886,6.099451e-7,0.0001689287],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00009224908,0.0003630891,0.3257117,0.006908178,0.0008425895,0.000009433389,0.00229341,0.0004653056,0.001373758,0.2886324,0.001509462,0.3717984],"study_design_scores_gemma":[0.001910999,0.0001991791,0.7788757,0.0005882181,0.0000788617,0.0002515639,0.000576926,0.004860774,0.0001014614,0.00760626,0.2038131,0.001136925],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8943899,0.102381,0.000001747151,0.000890584,0.00008077209,0.0003791965,0.0006146064,0.00001376216,0.00124847],"genre_scores_gemma":[0.5360432,0.4628691,0.00004505571,0.0005648581,0.00005970819,0.00001659634,0.00007676526,0.00002514711,0.0002994928],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.453164,"threshold_uncertainty_score":0.9999027,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02592247246638771,"score_gpt":0.2124975077115541,"score_spread":0.1865750352451664,"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."}}