{"id":"W4224216044","doi":"10.1002/tesq.3146","title":"Digital Storytelling With Youth From Refugee Backgrounds: Possibilities for Language and Digital Literacy Learning","year":2022,"lang":"en","type":"article","venue":"TESOL Quarterly","topic":"Digital Storytelling and Education","field":"Health Professions","cited_by":82,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Pedagogy; Digital storytelling; Literacy; Sociology; Digital literacy; Storytelling; Meaning-making; Meaning (existential); Language acquisition; Psychology; Mathematics education; Narrative; Linguistics","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":[0.006027634,0.0005954672,0.0004103575,0.001050733,0.00604903,0.008248411,0.001108875,0.001139374,0.0045345],"category_scores_gemma":[0.006167408,0.0002510455,0.0006309791,0.0007281902,0.00731209,0.003930737,0.007659508,0.002000993,0.0004214072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002055124,"about_ca_system_score_gemma":0.002497569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004464809,"about_ca_topic_score_gemma":0.008918888,"domain_scores_codex":[0.9971862,0.002067539,0.00007827405,0.0001380344,0.0001624368,0.0003676142],"domain_scores_gemma":[0.9962682,0.002372888,0.0002612395,0.0002231531,0.0002271226,0.0006474687],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00004784159,0.0001059987,0.00781788,0.0001953346,0.00001025656,0.002077445,0.9556233,0.00007286191,0.001150699,0.007108849,0.001169965,0.02461943],"study_design_scores_gemma":[0.00001122176,0.00009563691,0.002254108,0.0002707848,0.0000186916,0.001040421,0.9574443,0.0001386425,0.0007521564,0.001859264,0.0360957,0.00001906852],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9652733,0.00154319,0.005118915,0.004367293,0.0001335658,0.0001377542,0.0000937411,0.00007234244,0.02325991],"genre_scores_gemma":[0.9940941,0.0008265827,0.002349842,0.0002828498,0.00002415425,0.0000804638,0.00002910207,0.00001786066,0.002294951],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008248411,"threshold_uncertainty_score":0.03187758,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02558919819105339,"score_gpt":0.3224461669037149,"score_spread":0.2968569687126615,"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."}}