{"id":"W2956157517","doi":"10.1080/14649357.2019.1629197","title":"Gigs, Side Hustles, Freelance: What Work Means in the Platform Economy City/ Blight or Remedy: Understanding Ridehailing’s Role in the Precarious “Gig Economy”/ Labour, Gender and Making Rent with Airbnb/ The Gentrification of ‘Sharing’: From Bandit Cab to Ride Share Tech/ The ‘Sharing Economy’? Precarious Labor in Neoliberal Cities/ Where Is Economic Development in the Platform City?/ Shared Economy: WeWork or We Work Together","year":2019,"lang":"en","type":"article","venue":"Planning Theory & Practice","topic":"Sharing Economy and Platforms","field":"Business, Management and Accounting","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Gig economy; BATES; Work (physics); Farm workers; State (computer science); Precarious work; Economy; Sociology; Labour economics; Political science; Economics; Precarity; Law; Agriculture; Engineering; History; Archaeology","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":[0.003919674,0.0006303005,0.0003746061,0.00157915,0.01544884,0.02280838,0.002031483,0.004714081,0.01437572],"category_scores_gemma":[0.004710339,0.0005163882,0.0005280446,0.001852549,0.04089233,0.03574024,0.009803931,0.005931682,0.003048483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00697604,"about_ca_system_score_gemma":0.007372825,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02356994,"about_ca_topic_score_gemma":0.03967366,"domain_scores_codex":[0.9971501,0.001420321,0.00004994894,0.0003419425,0.0002950991,0.0007425855],"domain_scores_gemma":[0.996738,0.001410678,0.0002828013,0.0002374878,0.0003724351,0.0009586718],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00004200252,0.00006894115,0.005839682,0.0002647986,0.00001237099,0.000431557,0.4759792,0.0001130687,0.0002355303,0.4094332,0.07026286,0.03731694],"study_design_scores_gemma":[0.00000913846,0.0000216583,0.002969458,0.0006858851,0.000009956326,0.0001798375,0.6104879,0.0001990371,0.0001786738,0.1033876,0.2818405,0.00003032307],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1748969,0.02152453,0.01114814,0.3944501,0.003175156,0.00008705707,0.0003281563,0.0001993292,0.3941906],"genre_scores_gemma":[0.9098965,0.009179948,0.002275542,0.03059665,0.0006950441,0.0001256149,0.0001241821,0.0004028946,0.04670353],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02356994,"threshold_uncertainty_score":0.05061495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05787957851454964,"score_gpt":0.2620320982799544,"score_spread":0.2041525197654048,"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."}}