{"id":"W4408210769","doi":"10.1017/s0305741024001577","title":"Little to Lose: Exit Options and Attitudes towards Automation in Chinese Manufacturing","year":2025,"lang":"en","type":"article","venue":"The China Quarterly","topic":"Digital Economy and Work Transformation","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"University of Michigan","keywords":"Status quo; Automation; Worry; Business; Labour economics; China; Outsourcing; Work (physics); Marketing; Demographic economics; Economics; Anxiety; Political science; Engineering; Psychology; Market economy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001440416,0.0002110013,0.0001803687,0.0009321571,0.001620563,0.001439326,0.0002906008,0.0004755899,0.002809335],"category_scores_gemma":[0.002810462,0.0001437216,0.0002199655,0.000617188,0.002448996,0.0007575098,0.001189372,0.0005617729,0.00012236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001234711,"about_ca_system_score_gemma":0.0008319553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01399232,"about_ca_topic_score_gemma":0.01864334,"domain_scores_codex":[0.9992827,0.0001947943,0.00005077474,0.00006897657,0.0001972236,0.0002056191],"domain_scores_gemma":[0.997674,0.0006537208,0.0008836983,0.0001124819,0.0002342899,0.0004417862],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000153782,0.0001382584,0.8495201,0.00007324633,0.00003688948,0.0006489602,0.1365582,0.0001657116,0.002054926,0.001442285,0.000329764,0.008877848],"study_design_scores_gemma":[0.000007206453,0.0001075472,0.8413408,0.0000412882,0.00001309676,0.0001290547,0.1561551,0.0003663201,0.000282481,0.0003494335,0.001186426,0.00002128988],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992626,0.00001672476,0.00001405486,0.00006061943,9.211889e-7,0.000001760342,0.000004850093,4.563823e-7,0.0006378523],"genre_scores_gemma":[0.9997995,0.00001546967,0.00000660746,0.00001486725,9.820044e-7,0.000001098938,0.000005430796,2.2887e-7,0.0001558098],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01399232,"threshold_uncertainty_score":0.02782172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008300421866017246,"score_gpt":0.2891233955825798,"score_spread":0.2808229737165626,"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."}}