{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005532985,0.0000768688,0.0001398108,0.0002215541,0.0001712233,0.0001608927,0.0003209809,0.00006101287,0.00008309736],"category_scores_gemma":[0.0004595719,0.00007041803,0.00003741836,0.0007729523,0.0001013898,0.0007610221,0.0001104155,0.0001713109,0.00003348303],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001028151,"about_ca_system_score_gemma":0.0000177349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004164863,"about_ca_topic_score_gemma":0.00008428698,"domain_scores_codex":[0.9991543,0.00003879207,0.000290171,0.0001610041,0.0002208012,0.000134875],"domain_scores_gemma":[0.9992056,0.0002578239,0.0003062661,0.0001040925,0.0001058546,0.00002028961],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002175387,0.0003014285,0.8461171,0.0001264573,0.00003023669,5.998987e-7,0.08467125,0.0000386135,0.0006510942,0.02564739,0.03854913,0.003649187],"study_design_scores_gemma":[0.0004112699,0.00007168532,0.9468903,0.0005504107,0.00001323983,7.007947e-7,0.01264778,0.0001276592,0.000480244,0.02154506,0.01705074,0.0002108878],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9806035,0.000004341543,7.765294e-7,0.007735635,0.0003159916,0.0001823022,0.000001451273,0.00002469383,0.01113128],"genre_scores_gemma":[0.9974067,0.000003540851,0.00007117749,0.00009859697,0.0001241912,0.00001307963,0.000002894925,0.000008068925,0.002271797],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1007733,"threshold_uncertainty_score":0.2871564,"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."}}