{"id":"W4402614959","doi":"10.1108/ijm-11-2022-0521","title":"Intersectional analysis of the labour market impacts of COVID on women with young children and in low-skilled jobs","year":2024,"lang":"en","type":"article","venue":"International Journal of Manpower","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Memorial University of Newfoundland","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Pandemic; Differential (mechanical device); Demographic economics; Labour economics; Economics; Originality; Margin (machine learning); Intersectionality; Shock (circulatory); 2019-20 coronavirus outbreak; Psychology; Sociology; Medicine; Gender studies; Social psychology","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007192398,0.00009242682,0.0002686346,0.0006260888,0.00004918597,0.00001101487,0.000204397,0.0000443762,0.0009425871],"category_scores_gemma":[0.0001644892,0.00005181713,0.00009873808,0.0003497254,0.00007262059,0.000109703,0.00009586257,0.0003263501,0.000001424993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002193714,"about_ca_system_score_gemma":0.0001414075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002098223,"about_ca_topic_score_gemma":0.0006798822,"domain_scores_codex":[0.9985878,0.0001524551,0.0005311092,0.0000978552,0.0004990221,0.0001317145],"domain_scores_gemma":[0.9988532,0.0003379097,0.0003597159,0.00007608374,0.0003271083,0.00004598794],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001299705,0.0001006683,0.9854746,0.00004029661,0.003434992,0.00001726559,0.00605821,0.0001150555,0.00009370998,0.0008513397,0.002370634,0.0001435389],"study_design_scores_gemma":[0.0008108022,0.0001466358,0.9961742,0.0007836425,0.0001061132,0.00001291629,0.001172765,0.00004136014,0.00002675285,0.0002817755,0.000392985,0.00005001447],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941392,0.0001587737,0.0000250394,0.003193057,0.0007980332,0.000108478,0.00007802116,0.000004126252,0.001495291],"genre_scores_gemma":[0.9984744,0.0001451292,0.00001252959,0.0002755394,0.0001228913,0.000004549215,0.000002481119,0.000008308601,0.0009541454],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01069965,"threshold_uncertainty_score":0.9999707,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00946573314937962,"score_gpt":0.3479184909146324,"score_spread":0.3384527577652528,"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."}}