{"id":"W2957939939","doi":"10.1111/bjir.12485","title":"Uberizing the Legal Profession? Lawyer Autonomy and Status in the Digital Legal Market","year":2019,"lang":"en","type":"article","venue":"British Journal of Industrial Relations","topic":"Digital Economy and Work Transformation","field":"Social Sciences","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Autonomy; Flexibility (engineering); Legal profession; Legal service; Work (physics); Business; Legal status; Labour law; Service (business); Face (sociological concept); Law; Public relations; Labour economics; Political science; Marketing; Economics; Sociology; Management","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":[0.001768515,0.00007690284,0.0002053573,0.001682713,0.002773713,0.004345725,0.0006054605,0.0009176894,0.01617307],"category_scores_gemma":[0.01094153,0.0001214154,0.0001121095,0.001156263,0.004132275,0.003905471,0.003327749,0.001391388,0.0006963686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001341497,"about_ca_system_score_gemma":0.001750438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007554745,"about_ca_topic_score_gemma":0.01314566,"domain_scores_codex":[0.9981062,0.0004460342,0.00007020873,0.0001541635,0.0004486094,0.0007747721],"domain_scores_gemma":[0.9860838,0.004541256,0.004463173,0.0003192827,0.0007020326,0.003890445],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002592866,0.001106003,0.8584995,0.00005044316,0.00001591697,0.0007735094,0.06152953,0.0002562302,0.001363544,0.03450816,0.00214605,0.03949176],"study_design_scores_gemma":[0.0000292883,0.0001099325,0.8235254,0.00008478334,0.00000622674,0.0001888038,0.1598146,0.001185811,0.0002516558,0.007614451,0.007166446,0.0000225911],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9905002,0.00005100111,0.00006037247,0.000995493,0.000005100639,0.000005545653,0.00001861792,0.000001310577,0.008362431],"genre_scores_gemma":[0.999518,0.00001074056,0.000007725247,0.00002407579,0.00000385671,0.00000150185,0.000005035805,3.871729e-7,0.0004287509],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01617307,"threshold_uncertainty_score":0.05410427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01820090842037193,"score_gpt":0.2586252207600028,"score_spread":0.2404243123396309,"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."}}