{"id":"W2099293443","doi":"10.24124/c677/200826","title":"Gendering Local Governing: Canadian and Comparative Lessons – The Case of Metropolitan Vancouver","year":2008,"lang":"en","type":"article","venue":"Canadian Political Science Review","topic":"Gender Politics and Representation","field":"Social Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Metropolitan area; Legislature; Politics; Gender equity; Political science; Representation (politics); Equity (law); Variety (cybernetics); State (computer science); Local government; Public administration; Economic growth; Geography; Law; 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":[0.003327578,0.0002951675,0.0005890547,0.002298106,0.02842036,0.00789771,0.002444912,0.002073253,0.006511114],"category_scores_gemma":[0.004826111,0.0003413961,0.0002875425,0.007354778,0.007297311,0.001662774,0.003221123,0.002401108,0.000318646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1088768,"about_ca_system_score_gemma":0.09875704,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9953708,"about_ca_topic_score_gemma":0.9989317,"domain_scores_codex":[0.996381,0.001072008,0.00007741313,0.0002342968,0.0007478581,0.001487495],"domain_scores_gemma":[0.9959953,0.0009499828,0.0001495049,0.0001598073,0.001674065,0.001071333],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001615229,0.000163582,0.03430135,0.0006311979,0.000074244,0.004596258,0.3983607,0.001024783,0.0008425138,0.3068503,0.1088117,0.1441818],"study_design_scores_gemma":[0.00001960624,0.00003633708,0.03976222,0.0004634485,0.00004780684,0.0003895707,0.4787812,0.0003146717,0.0002706914,0.004885154,0.4749579,0.00007142245],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5101903,0.02986776,0.0005581682,0.06734598,0.0004666728,0.0001111859,0.0003827458,0.00003540093,0.3910418],"genre_scores_gemma":[0.9259707,0.01155525,0.0004826764,0.004161183,0.00005040977,0.00003593373,0.0001123049,0.00004117175,0.05759036],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1088768,"threshold_uncertainty_score":0.7899604,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.146759106502026,"score_gpt":0.3908298449872809,"score_spread":0.2440707384852549,"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."}}