{"id":"W3137484143","doi":"10.1017/9781108674355.009","title":"Divergence and Convergence in English and Canadian Administrative Law","year":2021,"lang":"en","type":"book-chapter","venue":"Cambridge University Press eBooks","topic":"Legal principles and applications","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Administrative law; Jurisdiction; Divergence (linguistics); Argument (complex analysis); Judicial review; Political science; Law; Convergence (economics); Suspect; Comparative law; Common law; Law and economics; Sociology; Economics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001037229,0.0001442077,0.0001807007,0.00005978506,0.0004951637,0.00007171663,0.0002074736,0.0002186569,0.00001683155],"category_scores_gemma":[0.00001945284,0.0001908486,0.00003476725,0.00001303293,0.0007255246,0.0001010915,0.0001667202,0.0002640228,0.000001709718],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001907708,"about_ca_system_score_gemma":0.0005718759,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.3014579,"about_ca_topic_score_gemma":0.3323472,"domain_scores_codex":[0.999139,0.00004081986,0.00009661388,0.0003625359,0.0001355875,0.0002255011],"domain_scores_gemma":[0.9992096,0.00006151113,0.00006467802,0.0001602697,0.0001437547,0.000360228],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003776642,0.000002089416,0.00007535431,0.00001296603,0.00001338092,0.0001142908,0.001544671,1.197214e-7,0.000001836911,0.9971326,0.0009511205,0.0001478203],"study_design_scores_gemma":[0.0001164857,0.000008945774,0.0002121608,0.00005550869,0.00002849563,0.000001027008,0.001348268,0.000004504584,0.00001507432,0.00005073972,0.9979472,0.0002116148],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001516614,0.00021951,0.000005311677,0.00009635153,0.00009976984,0.0002659288,0.0003309475,0.00002529676,0.9974403],"genre_scores_gemma":[0.1641492,0.000686698,0.00002740224,0.00008814056,0.00006660896,9.712924e-7,0.00001510136,0.000008223093,0.8349577],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9970818,"threshold_uncertainty_score":0.7782578,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03902714839844392,"score_gpt":0.2468867709113449,"score_spread":0.207859622512901,"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."}}