{"id":"W3047889056","doi":"10.1353/tech.2020.0064","title":"Machines That Cook or Women Who Cook? Lessons from Mali on Technology, Labor, and Women’s Things","year":2020,"lang":"en","type":"article","venue":"Technology and Culture","topic":"Agriculture and Rural Development Research","field":"Agricultural and Biological Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Narrative; Work (physics); Quarter (Canadian coin); Psychological intervention; Colonialism; Emerging technologies; Gender studies; Women's work; Economic growth; Sociology; Political science; History; Engineering; Economics; Psychology; Law; Art","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.002482734,0.0008915501,0.0005125082,0.001338807,0.01310659,0.008275992,0.0009939242,0.002512656,0.004301295],"category_scores_gemma":[0.00218346,0.0003488993,0.0001898669,0.001500503,0.02533319,0.007726002,0.005466954,0.003141881,0.0006075528],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007596032,"about_ca_system_score_gemma":0.002435516,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01413303,"about_ca_topic_score_gemma":0.03526167,"domain_scores_codex":[0.9986198,0.0008414077,0.00002021669,0.00008988283,0.00007937929,0.0003493173],"domain_scores_gemma":[0.998624,0.0009783681,0.0001481384,0.00004586449,0.00007027724,0.000133464],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00004057053,0.00001819409,0.001546598,0.0001563981,0.000003850604,0.0007871532,0.9176831,0.000028198,0.0002195817,0.06498369,0.003474348,0.01105833],"study_design_scores_gemma":[0.00000460302,0.00003689755,0.002293244,0.0005830351,0.000005915865,0.0002781254,0.8505263,0.00003890328,0.0002797065,0.009151232,0.1367872,0.00001497079],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5575071,0.09405835,0.001298833,0.1781399,0.000883624,0.00004638936,0.0001177148,0.00004567029,0.1679024],"genre_scores_gemma":[0.9556206,0.02231546,0.0002641627,0.006080674,0.0002634879,0.00003262206,0.00001955479,0.00002797917,0.01537541],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9868934,"threshold_uncertainty_score":0.05511332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01681791046701921,"score_gpt":0.2375336824605587,"score_spread":0.2207157719935395,"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."}}