{"id":"W2617184100","doi":"","title":"국가간 다문화정책 비교연구","year":2016,"lang":"ko","type":"article","venue":"한국인간복지실천연구","topic":"Educational Systems and Policies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Multiculturalism; Political science; Pluralism (philosophy); Government (linguistics); Cultural assimilation; Cultural diversity; Globalization; China; Sociology; Ethnic group; Economic growth; Law; Economics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003776385,0.0002434754,0.00025494,0.0001156306,0.0002206952,0.0002294473,0.001021454,0.0001397491,0.0008270288],"category_scores_gemma":[0.00009692091,0.0001613266,0.0001429137,0.0003444228,0.0001368002,0.0004839608,0.0002543332,0.0001038106,0.006948015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001110371,"about_ca_system_score_gemma":0.0003321512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007612834,"about_ca_topic_score_gemma":0.00006607325,"domain_scores_codex":[0.9979836,0.0001276173,0.0003977592,0.0004873399,0.0004390169,0.0005646889],"domain_scores_gemma":[0.998201,0.0003253256,0.000174198,0.0008878696,0.0001545738,0.0002570311],"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":[0.000005748145,0.0002027512,0.0299388,0.00005719498,0.00008414055,0.00001517139,0.00768022,0.00000305872,0.005135742,0.6557928,0.2189385,0.08214577],"study_design_scores_gemma":[0.0004306123,0.000123489,0.1275944,0.0003656294,0.00001487314,0.00005060031,0.00008698319,0.00008639432,0.001995795,0.008530579,0.8602237,0.0004970501],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5806479,0.006493188,0.071393,0.1960998,0.02595954,0.001023567,0.0002254184,0.0006447974,0.1175128],"genre_scores_gemma":[0.927982,0.0001439625,0.00111247,0.001261871,0.002008638,0.00002287438,0.000001480539,0.00002076385,0.06744588],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6472623,"threshold_uncertainty_score":0.9938252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02522196412488559,"score_gpt":0.2798232504769151,"score_spread":0.2546012863520295,"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."}}