{"id":"W2080159936","doi":"10.1177/0042098014553752","title":"Growth of rural migrant enclaves in Guangzhou, China: Agency, everyday practice and social mobility","year":2014,"lang":"en","type":"article","venue":"Urban Studies","topic":"Migration, Ethnicity, and Economy","field":"Social Sciences","cited_by":132,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Lethbridge","funders":"National Natural Science Foundation of China","keywords":"Agency (philosophy); China; Plea; Limiting; Economic growth; Economic geography; Scale (ratio); Immigration; Ethnography; Rural area; Business; Sociology; Geography; Political science; Economics","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":[],"consensus_categories":[],"category_scores_codex":[0.001523398,0.00009847365,0.0002750504,0.00005223624,0.0004180377,0.00001932119,0.0001075808,0.00006072811,0.0000190073],"category_scores_gemma":[0.001270397,0.0000882739,0.00005102115,0.0001465572,0.0005498533,0.0003344361,0.00006042108,0.00008724566,0.000004386507],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005797244,"about_ca_system_score_gemma":0.00004510897,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01017873,"about_ca_topic_score_gemma":0.02748055,"domain_scores_codex":[0.9988544,0.0003488277,0.0002621858,0.0001510579,0.000170617,0.0002129231],"domain_scores_gemma":[0.9991723,0.0004335501,0.0001469882,0.00008040947,0.0001360103,0.00003074477],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.00002272123,0.0001105338,0.2287524,0.0000714132,0.00005804977,4.671683e-7,0.7485652,5.896864e-7,0.00003814405,0.0159882,0.005175745,0.001216484],"study_design_scores_gemma":[0.0003536289,0.00007487639,0.8590213,0.00002457504,0.00004505657,4.058444e-7,0.1104032,0.00001063006,0.00005996768,0.01854566,0.01126883,0.0001918433],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9866202,0.003063304,0.00001432565,0.002143746,0.0001672189,0.0001852428,0.000004390726,0.00002285551,0.007778716],"genre_scores_gemma":[0.998223,0.0008523677,0.00009604584,0.0001043053,0.0002456049,0.00001713087,0.000001178295,0.00000436399,0.0004560007],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.638162,"threshold_uncertainty_score":0.9964126,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02670428286207596,"score_gpt":0.3147832605168026,"score_spread":0.2880789776547267,"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."}}