{"id":"W4393810602","doi":"10.5281/zenodo.6992806","title":"Globalization, Manufacturing, Regional Inequality, and Preferences for Redistribution: A Case Study of Ontario, Canada","year":2022,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Labor Movements and Unions","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Redistribution (election); Inequality; Globalization; Economic geography; Economics; Geography; Regional science; Political science; Mathematics; Market economy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006503512,0.0005273173,0.000597028,0.002917002,0.002418224,0.001531142,0.001735704,0.0006747484,0.00938502],"category_scores_gemma":[0.002729099,0.0003774104,0.0007803474,0.01237537,0.0006503292,0.0006943571,0.00135045,0.0008537918,0.001932643],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02690708,"about_ca_system_score_gemma":0.03510454,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9973482,"about_ca_topic_score_gemma":0.9987538,"domain_scores_codex":[0.9994861,0.00005159299,0.0000371699,0.00007161775,0.0001391915,0.0002143389],"domain_scores_gemma":[0.997601,0.0002117051,0.0002634712,0.0001658327,0.001388375,0.0003696902],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003612874,0.0001657935,0.22047,0.0007042479,0.0002190164,0.0005292665,0.003283482,0.002790726,0.0002049163,0.005243255,0.7499015,0.01612634],"study_design_scores_gemma":[0.0002084663,0.00002786222,0.743784,0.0006085562,0.0001452336,0.0001573347,0.008531782,0.00260338,0.0002079538,0.0006717736,0.2429468,0.000106879],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.1075034,0.001448796,0.000279032,0.001726844,0.00004092453,0.0001646402,0.8802577,0.0001004025,0.008478313],"genre_scores_gemma":[0.2037489,0.001811195,0.001200453,0.0003290348,0.00003184998,0.0003970438,0.7742932,0.00008707836,0.01810122],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02690708,"threshold_uncertainty_score":0.1952255,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05694076544320194,"score_gpt":0.2955252822377674,"score_spread":0.2385845167945654,"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."}}