{"id":"W4408306594","doi":"10.1097/naq.0000000000000662","title":"Leveraging State Legislation to Impact Workforce Shortages","year":2025,"lang":"en","type":"article","venue":"Nursing Administration Quarterly","topic":"Global Health Workforce Issues","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Registered Nurses' Association of Ontario; CARE Canada","funders":"","keywords":"Legislation; Workforce; Leverage (statistics); Economic shortage; Nursing shortage; Business; State (computer science); Public relations; Nursing; Economic growth; Political science; Medicine; Nurse education; Economics; Government (linguistics); Computer science; Law","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005751222,0.0002642304,0.0003169914,0.0002800431,0.001025616,0.00008468309,0.0001952532,0.0001899077,0.0002426943],"category_scores_gemma":[0.00007838788,0.0002643824,0.000085764,0.0007388955,0.00005113659,0.0003147193,0.000008150012,0.0004760327,0.0003407426],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000901049,"about_ca_system_score_gemma":0.0009248535,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001944437,"about_ca_topic_score_gemma":0.000215242,"domain_scores_codex":[0.9971468,0.0003883666,0.0008585273,0.0004528686,0.0003293675,0.0008240949],"domain_scores_gemma":[0.9984654,0.0002990055,0.0002257556,0.0004519733,0.0002582646,0.0002995768],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001260576,0.0003403567,0.07835856,0.0002390228,0.00006891493,0.00002022572,0.07873116,0.0007791009,0.001060475,0.01498959,0.1470543,0.6770977],"study_design_scores_gemma":[0.004491914,0.007904424,0.6206551,0.02235846,0.0002376764,0.00002179659,0.09814403,0.01234462,0.0009392623,0.036617,0.1939353,0.002350483],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8645312,0.00018877,0.04188209,0.01190749,0.002323936,0.001684785,0.00002968049,0.0004969802,0.07695504],"genre_scores_gemma":[0.9808745,0.000005228371,0.00153496,0.001399322,0.0002311053,0.0001064672,0.00008874344,0.00002638563,0.01573333],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6747472,"threshold_uncertainty_score":0.9999809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04788859860129936,"score_gpt":0.4832860227235459,"score_spread":0.4353974241222466,"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."}}