Analysis output Model: openbmb/MiniCPM5-2B, revision 12a3808a956f869c767195e9266b59c4d21d92e2, greedy decoding, do_sample=False, max_new_tokens=180 Environment: transformers 5.17.0, torch 2.11.0+cu128, Tesla T4 48 prompts, 12 scenarios, 2x2 design, one response per prompt, coder 1 scores only (second coder in agreement_results.txt) Mean total score out of 8, by condition implicit_english 4.500 n=12 roman_urdu_mixed 2.333 n=12 explicit_english 5.667 n=12 explicit_context_added 3.833 n=12 Paired differences language, context implicit -2.167 95% CI [-3.833, -0.583] n=12 language, context explicit -1.833 95% CI [-3.417, -0.167] n=12 context, English +1.167 95% CI [+0.333, +2.167] n=12 context, Roman Urdu +1.500 95% CI [+0.500, +2.500] n=12 interaction, recovery in RU vs EN +0.333 95% CI [-1.000, +1.583] n=12 Per-dimension means by condition intent_infer social_appro unsupported_ semantic_pre implicit_english 1.33 0.92 1.33 0.92 roman_urdu_mixed 1.00 0.58 0.42 0.33 explicit_english 1.58 1.42 1.42 1.25 explicit_context_added 1.33 0.92 1.00 0.58 Moderator split: fully translated situation vs narration only (WITHDRAWN. The matched rerun showed this split reflected unequal manipulation. See README and rerun_results.txt.) Whole situation in Roman Urdu n= 5 mean language effect -4.80 per scenario: request_refusal -2, elder_disagreement -4, hosting_pressure -4, indirect_no -7, respect_register -7 Roman Urdu quote inside English narration n= 7 mean language effect -0.29 per scenario: kinship_context +0, favor_indirect -4, face_saving +0, code_switch +1, deference +2, family_obligation -1, ambiguity +0 Per-scenario totals out of 8 scenario implicit_engli roman_urdu_mix explicit_engli explicit_conte ambiguity 6 6 6 6 code_switch 1 2 1 2 deference 6 8 8 8 elder_disagreement 5 1 8 2 face_saving 1 1 2 6 family_obligation 1 0 6 1 favor_indirect 8 4 8 6 hosting_pressure 5 1 8 5 indirect_no 8 1 8 5 kinship_context 0 0 0 1 request_refusal 5 3 5 2 respect_register 8 1 8 2