{"id":"W3144714517","doi":"","title":"Who benefits from new transportation infrastructure? Using accessibility measures to evaluate social equity in public transport provision","year":2012,"lang":"en","type":"article","venue":"eScholarship@McGill (McGill)","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Equity (law); Public transport; Business; Transport infrastructure; Social equality; Transport engineering; Public economics; Finance; Environmental economics; Economics; Engineering; Political science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007968962,0.0002682641,0.0003616514,0.001966141,0.0003361337,0.001954756,0.0004703498,0.0007061949,0.00233718],"category_scores_gemma":[0.02535865,0.0001292885,0.0005715975,0.002107028,0.001703068,0.003414075,0.001418371,0.0007578083,0.0002293931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001295555,"about_ca_system_score_gemma":0.0005603381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00648886,"about_ca_topic_score_gemma":0.01095789,"domain_scores_codex":[0.9951492,0.003318551,0.0002220335,0.0001927776,0.0008863671,0.0002309635],"domain_scores_gemma":[0.9877373,0.008362427,0.002103647,0.0003880228,0.0007256325,0.0006828492],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003795831,0.0002905968,0.8667198,0.0001001844,0.0003649642,0.0000883162,0.002390801,0.001906803,0.0001307247,0.01332231,0.003755856,0.11055],"study_design_scores_gemma":[0.00004936568,0.0008894972,0.9514652,0.0002301787,0.0001959784,0.0001946399,0.00971292,0.01072315,0.0004407454,0.020884,0.005159149,0.00005513231],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9617321,0.003059612,0.002634943,0.003412575,0.0001228314,0.00007933521,0.0005848247,0.00001617988,0.02835769],"genre_scores_gemma":[0.9984419,0.0002976388,0.0005429375,0.00009252172,0.00003145274,0.00002895658,0.00009457411,0.000002688078,0.0004674261],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007968962,"threshold_uncertainty_score":0.04214442,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09937116244246726,"score_gpt":0.3524648783008399,"score_spread":0.2530937158583727,"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."}}