{"id":"W2967698736","doi":"10.33137/jaste.v10i1.32915","title":"From Computational Thinking to Political Resistance","year":2019,"lang":"en","type":"article","venue":"Journal for Activist Science and Technology Education","topic":"Teaching and Learning Programming","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"National Science Foundation","keywords":"Deportation; Presidential election; Immigration; Politics; Constructive; Resistance (ecology); Enforcement; Presidential campaign; Mathematics education; Pedagogy; Sociology; Political science; Psychology; Presidential system; Law; Process (computing); Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.001609699,0.000455695,0.0001634859,0.000722311,0.003440142,0.007827738,0.0006884282,0.0009876889,0.004075944],"category_scores_gemma":[0.003353791,0.0001722615,0.000312744,0.0004252055,0.02295021,0.004925854,0.00413248,0.002813774,0.0004572667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002811187,"about_ca_system_score_gemma":0.002809842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002171027,"about_ca_topic_score_gemma":0.002059395,"domain_scores_codex":[0.998472,0.001126292,0.00002676567,0.0001360161,0.0001050677,0.0001337695],"domain_scores_gemma":[0.9981281,0.001418709,0.00009978367,0.0001127897,0.00007614619,0.0001644582],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003445294,0.0001017178,0.002913863,0.0002102268,0.00001155948,0.0006982537,0.3202806,0.0005292707,0.001460382,0.6378003,0.005108733,0.03085059],"study_design_scores_gemma":[0.00003507978,0.0000723179,0.002245857,0.00064416,0.00001523073,0.0007848732,0.3022732,0.001705162,0.002202175,0.4186897,0.2713039,0.00002838277],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4474921,0.003356625,0.0395741,0.05074017,0.0004415793,0.00009876079,0.00004242876,0.0001933759,0.4580609],"genre_scores_gemma":[0.9789516,0.001469053,0.004935263,0.001374345,0.00006113037,0.00007912645,0.00002081289,0.00008289037,0.01302586],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007827738,"threshold_uncertainty_score":0.02039671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00851498873945758,"score_gpt":0.3133403295012515,"score_spread":0.3048253407617939,"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."}}