{"id":"W3211681804","doi":"10.1177/08969205211055912","title":"After a Global Platform Leaves: Understanding the Heterogeneity of Gig Workers through Capital Mobility","year":2021,"lang":"en","type":"article","venue":"Critical Sociology","topic":"Digital Economy and Work Transformation","field":"Social Sciences","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Multinational corporation; Gig economy; Capital (architecture); Social capital; Ethnography; Work (physics); Salient; Business; Labour economics; Economics; Sociology; Political science; Labour law; Social science; Engineering; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002969235,0.0002961513,0.0003728486,0.002165899,0.009765046,0.008820638,0.001224735,0.001379797,0.005374031],"category_scores_gemma":[0.006407572,0.000208774,0.0002356821,0.001778281,0.01676076,0.009212329,0.008569395,0.001957955,0.0003699277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006652277,"about_ca_system_score_gemma":0.003123894,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04225618,"about_ca_topic_score_gemma":0.05141264,"domain_scores_codex":[0.9982927,0.0006021135,0.00003464402,0.0002896937,0.0001805424,0.0006003412],"domain_scores_gemma":[0.996582,0.001924913,0.0005011627,0.0002828749,0.0001731787,0.0005358923],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00005820369,0.00002877494,0.02888227,0.00004913967,0.000009438912,0.0005202983,0.9186264,0.0001341909,0.0004840776,0.03679053,0.0009977462,0.01341896],"study_design_scores_gemma":[0.000005336773,0.00002268318,0.01940615,0.00008667525,0.000007315515,0.00007477697,0.9482221,0.0002249283,0.0001194879,0.01765816,0.01415822,0.00001419438],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9599853,0.0003651605,0.001831751,0.003549413,0.00003449121,0.00002253436,0.00005395752,0.00001269647,0.03414479],"genre_scores_gemma":[0.9978935,0.00009753425,0.0001658394,0.0002325266,0.000009923902,0.00001314899,0.0000171419,0.000009116573,0.001561339],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04225618,"threshold_uncertainty_score":0.08402044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06914414421932702,"score_gpt":0.3484566578119229,"score_spread":0.2793125135925959,"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."}}