{"id":"W3030338287","doi":"10.1177/0885412220927691","title":"From Transportation Equity to Transportation Justice: Within, Through, and Beyond the State","year":2020,"lang":"en","type":"article","venue":"Journal of Planning Literature","topic":"Environmental Justice and Health Disparities","field":"Social Sciences","cited_by":251,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Equity (law); Environmental justice; Injustice; Transportation planning; Social justice; Scholarship; Public economics; Social equality; Economic Justice; State (computer science); Business; Public administration; Economics; Political science; Transport engineering; Economic growth; Engineering; Law and economics; Law; Computer science; Microeconomics","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":[],"consensus_categories":[],"category_scores_codex":[0.0002890347,0.00007695961,0.0001345893,0.00001860253,0.0003065567,0.0001489439,0.0001242423,0.0000666647,0.00002112271],"category_scores_gemma":[0.00005408321,0.00005516908,0.00003583104,0.000141993,0.00006448179,0.0005138878,0.000002916615,0.0003375254,0.000001535694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002359946,"about_ca_system_score_gemma":0.00005890908,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009159161,"about_ca_topic_score_gemma":0.0001907666,"domain_scores_codex":[0.9990442,0.00006823389,0.0002940524,0.00009566393,0.0003576938,0.0001401352],"domain_scores_gemma":[0.9994156,0.0001205041,0.0002121494,0.00003624096,0.00005171313,0.0001637388],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.000191178,0.00001261333,0.003053803,0.0001614808,0.00002116216,0.00006493978,0.987882,0.001042045,0.0005822248,0.001324361,0.005155716,0.0005085057],"study_design_scores_gemma":[0.001585157,0.000903556,0.3077656,0.001974621,0.001008834,0.0000062725,0.572673,0.0001147052,0.0005835209,0.01606224,0.09678318,0.0005393171],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9726122,0.004967299,0.0009888517,0.02029737,0.0004219319,0.0001336833,0.0002241087,0.00001153333,0.0003430243],"genre_scores_gemma":[0.9854159,0.0006908843,0.002813002,0.01010204,0.0008761028,0.000001510247,0.0000396985,0.000007543079,0.00005326854],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.415209,"threshold_uncertainty_score":0.2357817,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03594903118543771,"score_gpt":0.3513473245960654,"score_spread":0.3153982934106276,"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."}}