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AfriSyCo: Measuring Assertive Framing, Verification, and Wording Sensitivity Around African-Language Content

arXiv · AI, language, vision and robotics · article · Sep 15, 2026 · UTC

AfriSyCo studies answer switching around African-language factual content with two complementary layers: native-language follow-ups and a controlled cross-language factorial whose question, options, and target remain in the African language while the follow-up framing is English. We analyze 1,415 turn-1-correct model-language-item observations derived from 100 source questions across seven open-weight checkpoints and six languages; turn-1-correct denotes observed first-response accuracy, not demonstrated knowledge. Under native prompts, assertive endorsement produces 29.3 percentage points mor

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