{"id":"W7071021332","doi":"","title":"Recruiting Gen Z Workers to Ontario Municipalities: A Study of How Ontario Municipalities Can Improve Recruitment Strategies to Attract Gen Z Workers","year":2021,"lang":"en","type":"article","venue":"Scholarship@Western (Western University)","topic":"Generational Differences and Trends","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Local government; Obligation; Order (exchange); Best practice; Work (physics)","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":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.000791961,0.0004613023,0.0006413081,0.0004822834,0.0009365309,0.00108719,0.001141622,0.000233718,0.0002390074],"category_scores_gemma":[0.00008232481,0.0005303698,0.0002211556,0.000930325,0.0001585323,0.001202004,0.0006255442,0.0006592065,0.00002212764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002338523,"about_ca_system_score_gemma":0.003106378,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.4585403,"about_ca_topic_score_gemma":0.9990367,"domain_scores_codex":[0.9956802,0.0009246735,0.0004826297,0.0009097502,0.001065787,0.0009370188],"domain_scores_gemma":[0.9975209,0.0002294855,0.0002969262,0.0007745903,0.0005116595,0.0006664447],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001018552,0.0002280873,0.7108625,0.00001716801,0.0002462045,0.0001498532,0.2871179,0.0003849929,0.0001279425,0.0003498978,0.000002849645,0.0004107711],"study_design_scores_gemma":[0.0006064802,0.0003753474,0.5601609,0.0001717004,0.000129217,0.00000186374,0.4323842,7.597417e-8,0.0001567461,0.0000777654,0.00553033,0.0004053977],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944203,0.0000456127,0.00001934044,0.0009316833,0.000554253,0.001203864,0.00005942906,0.00008478892,0.00268068],"genre_scores_gemma":[0.84337,0.000009831404,0.0001716822,0.0001829179,0.0001146804,0.00002843905,0.00004035851,0.00003109533,0.156051],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5404963,"threshold_uncertainty_score":0.9999498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3213078944263179,"score_gpt":0.3874625699722016,"score_spread":0.06615467554588372,"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."}}