{"id":"W4406833058","doi":"10.1080/02722011.2024.2390327","title":"Political Dynamics and Infrastructure Allocation in the Canadian Context: A Case Study of Québec’s COVID-19 Recovery Plan (Bill 66)","year":2024,"lang":"en","type":"article","venue":"The American Review of Canadian Studies","topic":"Canadian Policy and Governance","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Politics; Context (archaeology); Plan (archaeology); Dynamics (music); Political science; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Public administration; Geography; Sociology; Law; Virology; Medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.001866202,0.0003584056,0.0003845475,0.002177219,0.02116167,0.005654801,0.001865208,0.001522106,0.00660304],"category_scores_gemma":[0.003766212,0.0002494765,0.0004269998,0.006722333,0.005785674,0.001460871,0.002232561,0.002144741,0.0002452974],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.2351833,"about_ca_system_score_gemma":0.1891043,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9987817,"about_ca_topic_score_gemma":0.9996482,"domain_scores_codex":[0.9975921,0.0005179278,0.00003206688,0.0001428388,0.0004456338,0.001269494],"domain_scores_gemma":[0.9973601,0.0006760878,0.000203302,0.00008681027,0.0009461225,0.0007275429],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002338404,0.0003119762,0.2050022,0.0006516655,0.0001701572,0.00532681,0.2114168,0.007173168,0.001256969,0.3092045,0.1370657,0.1221861],"study_design_scores_gemma":[0.00005294268,0.00007088346,0.2493824,0.0008150009,0.0001220915,0.0004703369,0.4119664,0.003822945,0.0004266768,0.004881646,0.3278362,0.000152533],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8021135,0.007358963,0.001344719,0.03198612,0.0001676787,0.0001865069,0.002114403,0.00003975227,0.1546884],"genre_scores_gemma":[0.9837275,0.002444924,0.0005533419,0.001108945,0.00001504091,0.00003322393,0.000250859,0.00001602922,0.01185014],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7648167,"threshold_uncertainty_score":0.8870789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04041997133349105,"score_gpt":0.3612390241248025,"score_spread":0.3208190527913115,"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."}}