{"id":"W2173740229","doi":"10.1145/1971681.1988996","title":"Enhancing the Social Issues Components in our Computing Curriculum","year":2010,"lang":"en","type":"article","venue":"","topic":"Open Source Software Innovations","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Royal University","funders":"China Scholarship Council; Home Office","keywords":"Curriculum; Information and Communications Technology; Computer science; Work (physics); Set (abstract data type); Social computing; Engineering ethics; Knowledge management; Social media; Sociology; Pedagogy; World Wide Web; 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":[0.0006451263,0.00009510324,0.0001135708,0.00008242827,0.0003716815,0.0002658913,0.001083269,0.00005144116,0.00001129675],"category_scores_gemma":[0.00008524373,0.00006893557,0.00003362526,0.000751489,0.00002646071,0.0003070792,0.0004759242,0.0004040901,0.00013103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001872909,"about_ca_system_score_gemma":0.0000314676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006538332,"about_ca_topic_score_gemma":0.0005269986,"domain_scores_codex":[0.9989517,0.00005526365,0.0002680945,0.000228352,0.0002362791,0.0002602752],"domain_scores_gemma":[0.9994223,0.00006618662,0.00007884483,0.000310413,0.00009735635,0.0000248792],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.000001707785,0.0005010259,0.1713963,0.0000196917,0.0000329843,0.00002674889,0.02541424,0.0001099811,0.06454129,0.6849202,0.01176156,0.04127427],"study_design_scores_gemma":[0.001525768,0.0000610687,0.7430809,0.00009613135,0.000009955753,0.00007785423,0.008404894,0.1798204,0.02556195,0.01222153,0.0277439,0.001395574],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8125756,0.000003985322,0.1729777,0.01175914,0.0007134969,0.0001398537,2.98364e-7,0.0002044596,0.001625461],"genre_scores_gemma":[0.9462036,1.394592e-7,0.05281812,0.0005598902,0.0002247107,0.000003569806,0.000001143036,0.00000583732,0.0001830142],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6726987,"threshold_uncertainty_score":0.2858711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01997494840208777,"score_gpt":0.3090828704618195,"score_spread":0.2891079220597317,"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."}}