{"id":"W2744940739","doi":"10.1177/1035304617722461","title":"Regulating work in the gig economy: What are the options?","year":2017,"lang":"en","type":"article","venue":"The Economic and Labour Relations Review","topic":"Digital Economy and Work Transformation","field":"Social Sciences","cited_by":534,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Realm; Gig economy; Scope (computer science); Work (physics); Legislation; Enforcement; Labour law; Business; Digital economy; Project commissioning; Law and economics; Public relations; Economics; Law; Publishing; Political science; Engineering; Computer science","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":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002254706,0.00007307481,0.0001359719,0.00001585636,0.002455985,0.001141107,0.0004625295,0.00003781379,0.0001958537],"category_scores_gemma":[0.00008714467,0.00004015291,0.00006191296,0.00005872519,0.0003095993,0.001867472,0.00002872632,0.0001531471,0.0003200386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007317575,"about_ca_system_score_gemma":0.0000708726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001862666,"about_ca_topic_score_gemma":0.00137705,"domain_scores_codex":[0.9992452,0.0002019907,0.0002744966,0.0001055057,0.00003242178,0.000140444],"domain_scores_gemma":[0.9990105,0.0002969312,0.0002651953,0.0003893455,0.00001321113,0.00002478415],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00000231097,0.000006152509,0.004670348,0.00003853884,0.00001495111,1.499036e-7,0.004463889,0.0002073852,3.779578e-9,0.8801246,0.001855345,0.1086164],"study_design_scores_gemma":[0.0001017438,0.000003404688,0.05438228,0.0008793674,0.00002796552,0.000001966866,0.006250124,0.00008431658,5.686155e-8,0.03343907,0.9047329,0.00009675031],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1361331,0.09810996,0.00004792084,0.3521731,0.0003874755,0.001711442,0.000009087711,0.00003132592,0.4113967],"genre_scores_gemma":[0.9354537,0.05939615,0.00001872353,0.001848245,0.000145464,0.0000822033,0.000003675956,0.000004473732,0.003047382],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9028776,"threshold_uncertainty_score":0.9998958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03053205613683724,"score_gpt":0.2859678771678078,"score_spread":0.2554358210309706,"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."}}