{"id":"W4365999179","doi":"10.1145/3579455","title":"A Matter of Time: Anticipation Work and Digital Temporalities in Refugee Humanitarian Assistance in Turkey","year":2023,"lang":"en","type":"article","venue":"Proceedings of the ACM on Human-Computer Interaction","topic":"Social Work Education and Practice","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Refugee; Temporality; Temporalities; Anticipation (artificial intelligence); Work (physics); Sociology; Scholarship; Situated; Resource (disambiguation); Computer-supported cooperative work; Political science; Computer science; Epistemology; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.002704757,0.0003076959,0.0002745047,0.002076043,0.005397482,0.005509506,0.0007301188,0.0006823871,0.002617992],"category_scores_gemma":[0.006021549,0.0002816984,0.0002246587,0.001843882,0.006530714,0.004074628,0.006075553,0.001041472,0.0002036451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003742802,"about_ca_system_score_gemma":0.003126587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01180831,"about_ca_topic_score_gemma":0.02008189,"domain_scores_codex":[0.9974357,0.001435143,0.0001328722,0.000254323,0.0002458743,0.0004960489],"domain_scores_gemma":[0.9963272,0.001711201,0.0009353777,0.0001852321,0.000261398,0.0005796289],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001121105,0.00005588365,0.03776823,0.000144214,0.000009835851,0.0008056472,0.9293133,0.0001605182,0.0004586142,0.007906852,0.0008253293,0.02243954],"study_design_scores_gemma":[0.000002902998,0.00002630271,0.02139387,0.0001043436,0.000006334041,0.0001760539,0.9682354,0.000123759,0.0001031544,0.001023006,0.008786027,0.00001875124],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9877939,0.0006621928,0.001301348,0.001017889,0.00003742854,0.00001881993,0.00003598259,0.0000104355,0.00912203],"genre_scores_gemma":[0.9991985,0.0001541285,0.000148395,0.00003588267,0.000005190815,0.00001011717,0.00001011426,0.000004079052,0.0004336058],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01180831,"threshold_uncertainty_score":0.02715605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06404443580549532,"score_gpt":0.374328745363235,"score_spread":0.3102843095577397,"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."}}