{"id":"W3093569432","doi":"10.1145/3415177","title":"Leveraging Peer Support for Mature Immigrants Learning to Write in Informal Contexts","year":2020,"lang":"en","type":"article","venue":"Proceedings of the ACM on Human-Computer Interaction","topic":"Innovative Teaching and Learning Methods","field":"Psychology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Software deployment; Peer learning; Immigration; Peer feedback; Computer science; Peer support; Negotiation; Literacy; Leverage (statistics); Public relations; Psychology; Pedagogy; Sociology; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001287952,0.0001995858,0.0002879128,0.0002371393,0.0001829216,0.00008757858,0.0007465256,0.000109682,0.00009287836],"category_scores_gemma":[0.001034457,0.0001647647,0.0001290609,0.0003053904,0.00002459486,0.0002644126,0.0002777485,0.001124415,0.00004620877],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000556558,"about_ca_system_score_gemma":0.000008481487,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004967916,"about_ca_topic_score_gemma":0.000001494995,"domain_scores_codex":[0.9985725,0.00006170681,0.0004554217,0.0003615046,0.000248248,0.0003006506],"domain_scores_gemma":[0.9988847,0.0001820441,0.0003662974,0.0001748677,0.0003402098,0.00005186708],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.003887611,0.0003763339,0.07807636,0.0004871576,0.000314597,0.000004580861,0.4486907,0.001708655,0.07370091,0.007181631,0.1240847,0.2614867],"study_design_scores_gemma":[0.004995393,0.004192848,0.6684499,0.001172654,0.00006951788,0.00006545677,0.01166858,0.005894637,0.02193877,0.001051478,0.2794453,0.001055474],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9852219,0.000003294532,0.002405677,0.005798468,0.0009972532,0.0004406107,0.000002179121,0.00009892538,0.005031662],"genre_scores_gemma":[0.9855426,1.454258e-7,0.00837952,0.003248031,0.0005735059,0.00004253616,0.00000708668,0.00003367996,0.002172889],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5903736,"threshold_uncertainty_score":0.6718908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09162598735691602,"score_gpt":0.4053014968539309,"score_spread":0.3136755094970149,"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."}}