{"id":"W4413588571","doi":"10.32920/29977291.v1","title":"Stories of Resilience: How Small Immigrant Businesses in Toronto’s Suburbs Have Adapted in the Face of Covid-19 Pandemic","year":2025,"lang":"en","type":"preprint","venue":"","topic":"Migration, Ethnicity, and Economy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Pandemic; Resilience (materials science); Immigration; Face (sociological concept); 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Psychological resilience; Business; Political science; Sociology; Virology; Psychology; Medicine; Social psychology; Social science; Infectious disease (medical specialty); Outbreak","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002366793,0.0008813572,0.0004980034,0.0009268497,0.02240996,0.006081138,0.002203061,0.002437909,0.002889592],"category_scores_gemma":[0.005319025,0.000539796,0.0005816488,0.001052617,0.01453221,0.004062043,0.00911996,0.004954355,0.0003394597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01599642,"about_ca_system_score_gemma":0.01217421,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4027257,"about_ca_topic_score_gemma":0.6404342,"domain_scores_codex":[0.9974977,0.001366043,0.00004945134,0.0001232358,0.000211967,0.0007515062],"domain_scores_gemma":[0.9960375,0.001071535,0.0003828867,0.0001604502,0.0003551109,0.001992417],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.00001822035,0.00001145401,0.004352935,0.0000316142,0.000006508963,0.001559426,0.989872,0.0000296357,0.0001870283,0.0006324103,0.001660315,0.001638383],"study_design_scores_gemma":[7.573472e-7,0.00001112638,0.002110075,0.00003493684,0.000003453901,0.000130183,0.9927327,0.0000204468,0.00003091925,0.00007422647,0.00484352,0.000007679084],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9796525,0.0009257708,0.0002129142,0.01092716,0.0001801466,0.00002833508,0.00007604638,0.00001800742,0.00797898],"genre_scores_gemma":[0.9952809,0.0007972758,0.0001248485,0.001059549,0.00002140013,0.000018493,0.00003582932,0.00001417178,0.00264759],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5972743,"threshold_uncertainty_score":0.8007631,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08030112007618206,"score_gpt":0.3575914720531848,"score_spread":0.2772903519770027,"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."}}