{"id":"W3199780818","doi":"10.5210/spir.v2021i0.12015","title":"DISEMBEDDEDNESS IN MACHINE LEARNING DATA WORK","year":2021,"lang":"en","type":"article","venue":"AoIR Selected Papers of Internet Research","topic":"Digital Economy and Work Transformation","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Commodity; Big data; Raw data; Politics; Work (physics); Profit (economics); Latin Americans; Artificial intelligence; Business; Computer science; Marketing; Economics; Engineering; Market economy; Political science; Microeconomics; Law","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.0161713,0.0002999805,0.0004734965,0.003098041,0.005839313,0.01118242,0.001833481,0.001398139,0.005809769],"category_scores_gemma":[0.04473404,0.0006981189,0.0005361041,0.003469309,0.0205627,0.02062069,0.01469531,0.0025543,0.0008586494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002596432,"about_ca_system_score_gemma":0.002774254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003211848,"about_ca_topic_score_gemma":0.003397187,"domain_scores_codex":[0.9795728,0.01181599,0.001364041,0.002935197,0.003228902,0.001082988],"domain_scores_gemma":[0.9356685,0.03847096,0.005111592,0.01633441,0.002483278,0.001931288],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001874075,0.0002343468,0.06980445,0.0003670308,0.0001015293,0.001392592,0.2603233,0.001840827,0.002190789,0.5075226,0.003181227,0.1528541],"study_design_scores_gemma":[0.00004471492,0.0002313067,0.0307043,0.001005941,0.00006194373,0.00292057,0.1665477,0.01222242,0.003632989,0.575363,0.2071735,0.00009177514],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8021551,0.003781385,0.0811851,0.02211291,0.0001236585,0.0001219377,0.000223203,0.0001709853,0.09012576],"genre_scores_gemma":[0.9885356,0.0005601286,0.005969864,0.0003993324,0.00004665366,0.00005154638,0.00008060315,0.00004477522,0.004311524],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9941607,"threshold_uncertainty_score":0.08552301,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06691643047326133,"score_gpt":0.3690679848839477,"score_spread":0.3021515544106863,"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."}}