{"id":"W4292451703","doi":"10.3390/recycling7040053","title":"Unpicking the Gender Gap: Examining Socio-Demographic Factors and Repair Resources in Clothing Repair Practice","year":2022,"lang":"en","type":"article","venue":"Recycling","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Social Sciences and Humanities Research Council of Canada; Mitacs; University of Alberta","keywords":"Clothing; Context (archaeology); Enabling; Reuse; Consumption (sociology); Business; Product (mathematics); Engineering; Psychology; Sociology; Political science; Geography; Waste management","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003455896,0.0002281416,0.0003744162,0.001054946,0.001336044,0.001474467,0.0007016828,0.0006854783,0.005163286],"category_scores_gemma":[0.009641147,0.0002566756,0.0004441267,0.0009253778,0.001331027,0.00195048,0.001406385,0.0007355132,0.0005127877],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008932516,"about_ca_system_score_gemma":0.00107068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01692924,"about_ca_topic_score_gemma":0.02850264,"domain_scores_codex":[0.9986497,0.0005270747,0.00009259157,0.0001780316,0.000280196,0.0002723858],"domain_scores_gemma":[0.9940451,0.002969665,0.001617528,0.000187942,0.000476216,0.0007034493],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001074418,0.0001452263,0.9597175,0.00008749148,0.00003628218,0.0002431409,0.02850807,0.00003095245,0.0001784105,0.0008425139,0.0005957725,0.009507247],"study_design_scores_gemma":[0.000006226135,0.0001404607,0.918937,0.0001510411,0.00002285012,0.0002220311,0.07765388,0.0002154344,0.00007205867,0.0004596003,0.002106212,0.00001327867],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952872,0.000773986,0.0001609775,0.0006252357,0.00003525751,0.00002229027,0.000152252,0.000001654302,0.002941207],"genre_scores_gemma":[0.9990506,0.0002050624,0.0001003037,0.0001606425,0.00001148837,0.00001965623,0.00005532955,0.000002392945,0.0003945494],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01692924,"threshold_uncertainty_score":0.03366143,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04030292654677536,"score_gpt":0.2548562602893829,"score_spread":0.2145533337426075,"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."}}