{"id":"W2081707276","doi":"10.1080/14927713.2008.9651406","title":"Assessment of territorial justice using geographic information systems: A case study of distributional equity of golf courses in Calgary, Canada","year":2008,"lang":"en","type":"article","venue":"Leisure/Loisir","topic":"Environmental Justice and Health Disparities","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"University of Illinois at Urbana-Champaign","keywords":"Disadvantaged; Equity (law); Ethnic group; Environmental justice; Census; Geography; Economic Justice; Demographic economics; Socioeconomic status; Economic growth; Socioeconomics; Political science; Regional science; Sociology; Demography; Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.001810417,0.0002762127,0.0003340925,0.002290975,0.007158009,0.002354982,0.001324853,0.0005827775,0.001240646],"category_scores_gemma":[0.00446606,0.0002018284,0.000299549,0.006696977,0.002117896,0.0007118573,0.001808892,0.0008589485,0.00006933149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03779183,"about_ca_system_score_gemma":0.04265228,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.991267,"about_ca_topic_score_gemma":0.9961511,"domain_scores_codex":[0.9981993,0.0004862513,0.00006854839,0.0001250678,0.0004285967,0.0006921234],"domain_scores_gemma":[0.9975283,0.0005965318,0.0003188849,0.0001339376,0.001014092,0.0004082449],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007948596,0.0002877195,0.8809261,0.0001258215,0.00007845405,0.004168739,0.06795993,0.001885744,0.0004460185,0.002805922,0.002504354,0.03873165],"study_design_scores_gemma":[0.00001612325,0.0001010393,0.6646738,0.0001657636,0.00005580154,0.0005402806,0.3223933,0.004722606,0.0004062435,0.0004303084,0.006450009,0.00004476513],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965544,0.0001403074,0.0001226758,0.0004223243,0.00000283295,0.00005099122,0.0001789132,0.000002759881,0.00252485],"genre_scores_gemma":[0.9990692,0.0001593706,0.0002645822,0.00004475725,0.00000149637,0.00001180359,0.00006718833,0.000001528251,0.0003799861],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03779183,"threshold_uncertainty_score":0.2742002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04470216533244653,"score_gpt":0.3560475112358588,"score_spread":0.3113453459034123,"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."}}