{"id":"W4323075474","doi":"10.1111/gec3.12681","title":"Addressing the need for more nuanced approaches towards transit‐induced gentrification: A case for a complex systems thinking framework","year":2023,"lang":"en","type":"article","venue":"Geography Compass","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of Waterloo","funders":"","keywords":"Gentrification; Scholarship; Economic geography; Sociology; Politics; Public transport; Perspective (graphical); Neighbourhood (mathematics); Work (physics); Process (computing); Regional science; Political economy; Political science; Economics; Economic growth; Transport engineering; Computer science; Engineering","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.001698715,0.0001992937,0.0003499368,0.000159846,0.002825508,0.0004589239,0.0006204178,0.000187351,0.0000119224],"category_scores_gemma":[0.00007557226,0.0001610811,0.0004356888,0.001390891,0.0003588159,0.0002091367,0.00001719211,0.0002065079,0.000001803639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003539188,"about_ca_system_score_gemma":0.0001169616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001855618,"about_ca_topic_score_gemma":0.0005243486,"domain_scores_codex":[0.9978776,0.0001603469,0.0004178675,0.0004643644,0.0004497778,0.0006300641],"domain_scores_gemma":[0.9984702,0.0005856368,0.0001964131,0.0004148496,0.000205159,0.0001277805],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.001436109,0.001219665,0.2103746,0.00388299,0.002076753,0.0001983555,0.4852931,0.00579565,0.001030002,0.1716508,0.01410841,0.1029336],"study_design_scores_gemma":[0.004535219,0.0002242645,0.5182728,0.0006800991,0.0009598747,0.00002102653,0.2687857,0.08692504,0.000335802,0.06897427,0.04818096,0.002105033],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8308425,0.0006892701,0.1489825,0.01184232,0.001141521,0.004906965,0.0003130377,0.0007392669,0.0005426424],"genre_scores_gemma":[0.9953143,0.000006880508,0.002702883,0.000152814,0.0006312393,0.001007428,0.0001386072,0.00002394986,0.00002189305],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3078981,"threshold_uncertainty_score":0.9984727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3225439673591536,"score_gpt":0.3858365661380682,"score_spread":0.06329259877891458,"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."}}