{"id":"W4366548927","doi":"10.1145/3544548.3581355","title":"“We need to do more... I need to do more”: Augmenting Digital Media Consumption via Critical Reflection to Increase Compassion and Promote Prosocial Attitudes and Behaviors","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Media Influence and Health","field":"Arts and Humanities","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Prosocial behavior; Empathy; Psychology; Compassion; Reflection (computer programming); Critical reflection; Session (web analytics); Social psychology; Computer science; Pedagogy","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002184146,0.0004745142,0.0002049586,0.0003912428,0.0006860979,0.001785104,0.0006286198,0.0006155323,0.004890819],"category_scores_gemma":[0.007396899,0.0001956906,0.0004250274,0.0002283941,0.0009394707,0.001837538,0.001699073,0.0009247653,0.0009460485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002711058,"about_ca_system_score_gemma":0.0006093108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003098974,"about_ca_topic_score_gemma":0.0005938901,"domain_scores_codex":[0.9989968,0.0006297754,0.00002697037,0.0001248578,0.0001182979,0.00010343],"domain_scores_gemma":[0.9968927,0.002004079,0.0003224026,0.0003213935,0.0001548465,0.0003045512],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002123202,0.007343472,0.01553985,0.002934439,0.0002388593,0.0004286018,0.07010652,0.0007360885,0.09626885,0.005328042,0.01053894,0.7884132],"study_design_scores_gemma":[0.002192802,0.02674457,0.2384047,0.00631999,0.00256056,0.00372898,0.1395239,0.01474587,0.2426654,0.0465373,0.2758213,0.0007545829],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9347661,0.0008744931,0.03541468,0.003351478,0.0002296242,0.0004875919,0.00007002342,0.0007526404,0.02405331],"genre_scores_gemma":[0.9295751,0.001028908,0.06089837,0.001121024,0.00009293746,0.0005107871,0.00008575807,0.0001699505,0.006517084],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004890819,"threshold_uncertainty_score":0.01636147,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08820829697569872,"score_gpt":0.3747396926037454,"score_spread":0.2865313956280467,"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."}}