{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006611334,0.00009267184,0.0003099112,0.0000844862,0.000257891,0.000009608129,0.0001299355,0.00007868117,0.00001384395],"category_scores_gemma":[0.00009532319,0.00009594893,0.00003227402,0.0002295858,0.0002337926,0.0003069727,0.0000611795,0.0001249786,1.114987e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004694769,"about_ca_system_score_gemma":0.001501275,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9589382,"about_ca_topic_score_gemma":0.8342625,"domain_scores_codex":[0.9979316,0.0002235547,0.0006458566,0.0001004345,0.0008649622,0.000233618],"domain_scores_gemma":[0.9990532,0.0002326769,0.0003923152,0.0001191147,0.0001215194,0.00008120653],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002425075,0.0005240826,0.9836631,0.001113441,0.00002934371,0.00008007169,0.005041329,0.001137643,0.00005087457,0.008202488,0.00009692125,0.00003649612],"study_design_scores_gemma":[0.001369671,0.0003194444,0.7593163,0.0003983889,0.0002230504,0.00004771993,0.2362038,0.001131146,0.00007680618,0.00001844111,0.0006682333,0.000226957],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978465,0.0001111732,0.00008502381,0.00002618359,0.0007078114,0.0005344757,0.0001852774,0.000005333041,0.00049815],"genre_scores_gemma":[0.9996719,0.00009055022,0.00005908323,0.00001069121,0.0001230173,0.00001660759,0.0000213057,0.000003290799,0.000003574694],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2311625,"threshold_uncertainty_score":0.3912683,"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."}}