{"id":"W4247281174","doi":"10.32920/14664153","title":"Unemployed women in neo-liberal Canada: an intersectional analysis of social well-being","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Intersectionality; Context (archaeology); Identity (music); Gender studies; Health care; Sociology; Social identity theory; Empowerment; Demographic economics; Political science; Economic growth; Economics; Geography; Social group; Social science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.00184459,0.000451518,0.0006557698,0.003170277,0.02545914,0.006018801,0.001212382,0.0006268875,0.002578936],"category_scores_gemma":[0.002036667,0.000329126,0.0003581048,0.005815125,0.006913722,0.001536648,0.007978701,0.001616716,0.0001296431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05985688,"about_ca_system_score_gemma":0.05218196,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9796118,"about_ca_topic_score_gemma":0.9922679,"domain_scores_codex":[0.9982577,0.0003496654,0.00003643524,0.0001003884,0.0003884734,0.0008673909],"domain_scores_gemma":[0.9987171,0.0002467851,0.0001524355,0.00004050348,0.0003271377,0.0005161095],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00007780534,0.00002485585,0.08635029,0.00004585156,0.00001314938,0.0006847818,0.8992501,0.00009311282,0.0003484736,0.003941913,0.0008680571,0.008301604],"study_design_scores_gemma":[0.000002452703,0.00001220248,0.05139021,0.00005102343,0.000007158813,0.0000713035,0.9414667,0.0001201342,0.00005359687,0.000245894,0.006562156,0.00001716313],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908651,0.0004089737,0.000123971,0.0008683782,0.00001117321,0.00002383897,0.0001084197,0.00000308141,0.00758711],"genre_scores_gemma":[0.9972818,0.0003859265,0.0001319489,0.0001409016,0.000003274332,0.00001508606,0.00007614883,0.00000388073,0.001961065],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05985688,"threshold_uncertainty_score":0.4342941,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03254566296638237,"score_gpt":0.3716303696218813,"score_spread":0.3390847066554989,"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."}}