{"id":"W7113469192","doi":"","title":"Addressing the Fairness of Municipal User Fee Policy","year":2021,"lang":"en","type":"other","venue":"TSpace","topic":"Local Government Finance and Decentralization","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Toronto; Trent University; Australian Government","keywords":"Government (linguistics); Corporate governance; User fee; Work (physics); Entitlement (fair division); Order (exchange)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01906386,0.00032685,0.000824018,0.001275042,0.005097521,0.009087119,0.001894244,0.006421488,0.0242294],"category_scores_gemma":[0.08991443,0.0003182667,0.0004202668,0.002361509,0.004611787,0.006045837,0.006534251,0.005384885,0.001739787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01244417,"about_ca_system_score_gemma":0.01567612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02445431,"about_ca_topic_score_gemma":0.0244688,"domain_scores_codex":[0.9766008,0.0114414,0.0005765149,0.002032253,0.004747198,0.00460184],"domain_scores_gemma":[0.9706932,0.01681964,0.002265265,0.004252333,0.004410556,0.001559149],"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":[0.00004341127,0.00001622956,0.0009454582,0.00002307557,0.00001026307,0.00003643834,0.0006564105,0.001108274,0.0001060472,0.9710954,0.01319548,0.01276338],"study_design_scores_gemma":[0.00004961535,0.00002571927,0.002252744,0.0001334803,0.00002412924,0.00003596899,0.001002697,0.005896387,0.0005992823,0.8953773,0.09457886,0.00002382453],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.09447978,0.00270925,0.03122884,0.1309139,0.0008522847,0.0001216232,0.0004730217,0.000211765,0.7390095],"genre_scores_gemma":[0.9509826,0.0004417937,0.002683362,0.006769291,0.0005922467,0.00007399425,0.0000632683,0.00010333,0.03829012],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.02445431,"threshold_uncertainty_score":0.1008205,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1120009161715636,"score_gpt":0.4297469701921757,"score_spread":0.3177460540206121,"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."}}