{"id":"W2891685369","doi":"10.1177/0896920518792615","title":"The Legal Construction of Precarity: Lessons from the Construction Sectors in Beijing and Delhi","year":2018,"lang":"en","type":"article","venue":"Critical Sociology","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Precarity; Beijing; State (computer science); Structuring; Resistance (ecology); Political science; Sociology; Informal sector; Economy; Political economy; Gender studies; Economic growth; Law; Economics; China","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":[0.003128353,0.0003289971,0.0005036754,0.00207738,0.01278142,0.007887782,0.002139724,0.002969649,0.002953854],"category_scores_gemma":[0.006714302,0.0004645749,0.000306894,0.004424688,0.04058843,0.004290226,0.01029056,0.003364661,0.0001617533],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02231055,"about_ca_system_score_gemma":0.01005014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.12672,"about_ca_topic_score_gemma":0.1775044,"domain_scores_codex":[0.9965333,0.001574415,0.0001567952,0.0002857789,0.0005509481,0.000898712],"domain_scores_gemma":[0.9941394,0.003919989,0.0007223318,0.0006144392,0.0002424063,0.0003615379],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00004611736,0.00004537537,0.01907045,0.0001518496,0.00001773015,0.005391725,0.577717,0.0006304506,0.0008103654,0.3825201,0.0008315407,0.01276733],"study_design_scores_gemma":[0.00005129942,0.0001017977,0.05624046,0.0004395828,0.00004149203,0.001191224,0.773275,0.001033047,0.001344346,0.09267186,0.07352284,0.00008719654],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9086152,0.001284544,0.0009926854,0.007015029,0.00003153522,0.00005202899,0.00002996486,0.00001200311,0.08196712],"genre_scores_gemma":[0.9978612,0.0002090227,0.00009482247,0.0001192777,0.000005791996,0.00001220819,0.000008110907,0.000003091074,0.001686473],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.12672,"threshold_uncertainty_score":0.2519649,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06701704622146523,"score_gpt":0.4445732869578569,"score_spread":0.3775562407363916,"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."}}