{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006879397,0.0002260049,0.0004779602,0.0009907,0.001170251,0.004361736,0.0014846,0.002803257,0.003320262],"category_scores_gemma":[0.006235453,0.0001831426,0.0003360903,0.001245267,0.006259536,0.003939325,0.002376395,0.002317194,0.0006705128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003046182,"about_ca_system_score_gemma":0.007187412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01441031,"about_ca_topic_score_gemma":0.0192167,"domain_scores_codex":[0.9965784,0.001584038,0.0001887357,0.0002369641,0.0009780155,0.0004338204],"domain_scores_gemma":[0.9955503,0.00253249,0.0005991569,0.0002274371,0.0008227639,0.0002678297],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00005814792,0.0001460915,0.003226356,0.007331382,0.00004749757,0.0003734727,0.004962637,0.001141527,0.001127312,0.5377348,0.02391476,0.419936],"study_design_scores_gemma":[0.00002222863,0.000112693,0.01011674,0.01594309,0.00005265163,0.0004027807,0.009677143,0.0004136197,0.0007092843,0.08173807,0.8807717,0.00003996791],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.02206168,0.7520013,0.003622633,0.1181959,0.001655513,0.00005918572,0.00005035085,0.00003144794,0.102322],"genre_scores_gemma":[0.3242568,0.6286199,0.003945669,0.02690074,0.00161554,0.000138175,0.00005993277,0.00002138757,0.01444183],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01441031,"threshold_uncertainty_score":0.0363822,"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."}}