{"id":"W7099955771","doi":"","title":"THE RESPONSE OF THE MUNCIPAL PUBLIC SERVICE SECTOR TO THE CHALLENGE OF IMMIGRANT SETTLEMENT","year":2000,"lang":"en","type":"article","venue":"","topic":"Pasture and Agricultural Systems","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Immigration; Citizenship; Settlement (finance); Public sector; Public service; Service (business)","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":[0.0007856601,0.0001077886,0.0001305344,0.000002550398,0.0003234,0.0000354801,0.0007593166,0.00004311558,0.0007243101],"category_scores_gemma":[0.00003603246,0.00001570299,0.000122877,0.0005094134,0.0000391562,0.00004103324,0.00009371289,0.0000778805,0.00004569403],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001361083,"about_ca_system_score_gemma":0.000007966612,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001899319,"about_ca_topic_score_gemma":0.02218231,"domain_scores_codex":[0.9986643,0.0003364367,0.000273682,0.0001488963,0.0003472993,0.0002294492],"domain_scores_gemma":[0.9992297,0.0003739993,0.00008920171,0.0001417578,0.0001113048,0.0000540696],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009336111,0.0003623425,0.003522052,0.00002700074,0.0001592406,0.000001352136,0.005930142,0.00004999614,0.8173146,0.002945153,0.03479062,0.1339639],"study_design_scores_gemma":[0.00008040972,0.0002081253,0.3841193,0.00002178664,0.000007903805,0.000002868811,0.002397733,0.000009726121,0.004495373,0.00004756259,0.6085229,0.00008632904],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.841949,0.0002209156,6.901325e-8,0.1551394,0.0000880408,0.0003859232,0.00005597261,0.00001238223,0.002148283],"genre_scores_gemma":[0.9962573,0.0000366963,0.000001904658,0.0008610906,0.0001752089,0.0000322949,0.000003924314,4.334541e-7,0.002631167],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8128192,"threshold_uncertainty_score":0.9956603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0270020752732754,"score_gpt":0.2085617304217165,"score_spread":0.1815596551484411,"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."}}