{"id":"W3142456158","doi":"10.36902/sjesr-vol4-iss1-2021(98-118)","title":"Sociolinguistic Engineering of English Semantics as a tool for Population Indoctrination, Subjugation and Control","year":2021,"lang":"en","type":"article","venue":"Sir Syed Journal of Education & Social Research (SJESR)","topic":"Multilingual Education and Policy","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Indoctrination; Terminology; Population; Glossary; Sociology; Ideology; Pedagogy; Linguistics; Political science; Law; Politics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003607135,0.0003471116,0.0002566391,0.00193444,0.003756427,0.006073344,0.0004445638,0.000657475,0.001408209],"category_scores_gemma":[0.004157797,0.0001660043,0.0001626736,0.001055557,0.01875424,0.004774407,0.001894016,0.001866192,0.0001442233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003991207,"about_ca_system_score_gemma":0.002637434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005092145,"about_ca_topic_score_gemma":0.006966329,"domain_scores_codex":[0.9967963,0.002545732,0.0001235986,0.0001099752,0.000305255,0.0001191117],"domain_scores_gemma":[0.9966431,0.002477173,0.0002517046,0.0002056317,0.0003374581,0.00008492653],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001381735,0.00001232329,0.0006407859,0.00004771569,0.000001828611,0.0002960022,0.1151303,0.000137273,0.0005039188,0.8724539,0.001265009,0.009497176],"study_design_scores_gemma":[0.00001511726,0.000124734,0.007847974,0.0004913288,0.00002172552,0.001184803,0.263447,0.00400624,0.002887161,0.3697072,0.3502,0.00006684106],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3315043,0.005709821,0.09823123,0.02132092,0.001052694,0.0002406957,0.0001502454,0.0001401834,0.5416499],"genre_scores_gemma":[0.9862591,0.0005582733,0.005876211,0.0002252079,0.00007634021,0.00004604139,0.00001800477,0.00003989771,0.006900991],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006073344,"threshold_uncertainty_score":0.02895832,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07674321365269335,"score_gpt":0.515063332543326,"score_spread":0.4383201188906327,"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."}}