An analysis of MMLU found that 28% of its questions require culturally sensitive knowledge and that 84.9% of its geography questions concern North America or Europe; model rankings change depending on whether the culturally sensitive questions are included, so machine-translated versions distort multilingual comparisons.

SocioLens project,

Claim LD06-SL-C11 (v1.0)

Provenance and status

Claim type: Estimate
Publication status: Eligible for publication, with qualifiers: institutional position
Verification state: Checked against the abstract of the primary source only. Who checked this claim is not recorded for it; claim checks so far were AI-led, and no person has checked claims against their sources.
Does not license: A judgement on multilingual benchmarks other than MMLU
Limitations: Read in abstract only; authors’ lab develops models; the full text, checked for this point only, estimates the 28% from a 2,850-question annotated sample
Source (as cited): Singh, Romanou, Fourrier, Adelani, Ngui, Vila-Suero et al., “Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation,” arXiv:2412.03304 (v2), 2025
Source type: Preprint (recorded as “Preprint”)
Institutional position: AI developer-affiliated research lab (Cohere For AI) with academic co-authors
Maturity of the evidence: Emerging evidence
Recorded date: 15 October 2026
Currentness / correction: This is the current version. No correction or concern is recorded on its sources.

Sources this version cites

Singh, Romanou, Fourrier, Adelani, Ngui, Vila-Suero et al., “Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation,” arXiv:2412.03304 (v2), 2025 (Preprint)
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Version

This page shows version v1.0. Its record never changes, even when newer evidence arrives; the site may add a note to the page or withhold a figure not cleared for public use.

This pinned version is also the current version.

Versions: v1.0 · current

Raw record: every recorded field, with its coded values

All 25 canonical Claim fields, verbatim, with the coded values derived from them. The plain-language labels above are read from these.

Claim type (coded): ESTIMATE (as printed: “ESTIMATE”)
Publication status (coded): ELIGIBLE (INSTITUTIONAL_POSITION) (as printed: “ELIGIBLE WITH INSTITUTIONAL-POSITION QUALIFIER”)
Verification state (coded): CONTENT_VERIFIED_PRIMARY (ABSTRACT_ONLY)
Source type (coded): PREPRINT
Maturity (coded): EMERGING

#	Canonical field	Canonical value (verbatim)	Normalized (Claim Value Vocabulary v1.0.2)
1	CLAIM ID	LD06-SL-C11	—
2	PUBLIC-FACING CLAIM	An analysis of MMLU found that 28% of its questions require culturally sensitive knowledge and that 84.9% of its geography questions concern North America or Europe; model rankings change depending on whether the culturally sensitive questions are included, so machine-translated versions distort multilingual comparisons.	—
3	CLAIM TYPE	ESTIMATE	base_types: ESTIMATE
4	RESEARCH STRAND	A — Benchmark validity and measurement	—
5	MATURITY	EMERGING	states: EMERGING
6	SOURCE	Singh, Romanou, Fourrier, Adelani, Ngui, Vila-Suero et al., “Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation,” arXiv:2412.03304 (v2), 2025	source_ids: SRC-SL-SINGH-ET-AL-GLOBAL-MMLU-ARXIV-2412-03304
7	SOURCE TYPE	Preprint	classes: PREPRINT
8	INSTITUTIONAL POSITION	AI developer-affiliated research lab (Cohere For AI) with academic co-authors	—
9	SCOPE	MMLU and translations into 42 languages	—
10	DESIGN	Annotation of cultural and regional knowledge; evaluation of models on full and subset versions	—
11	SAMPLE / DATASET	MMLU questions, annotated by professional and community annotators	—
12	MODEL / TOOL / VERSION	State-of-the-art open and proprietary models as of late 2024	—
13	COMPARATOR	Culturally sensitive versus culturally agnostic subsets	—
14	MAIN RESULT	28% of questions culturally sensitive; 84.9% of geographic questions North American or European; rankings shift between subsets	—
15	INFERENTIAL TARGET	Whether an English-made benchmark measures the same thing across languages and regions	—
16	DOES NOT LICENSE	A judgement on multilingual benchmarks other than MMLU	—
17	VERIFICATION STATE	CONTENT VERIFIED ABSTRACT	state: CONTENT_VERIFIED_PRIMARY · qualifiers: ABSTRACT_ONLY · verified_by: UNKNOWN
18	LIMITATIONS	Read in abstract only; authors’ lab develops models; the full text, checked for this point only, estimates the 28% from a 2,850-question annotated sample	—
19	CONTRADICTORY / SUPPORTING SOURCES	Compare the cultural biases found in ThaiExam: LD06-SL-C01	—
20	GEOGRAPHY / LANGUAGE	Global / multilingual	—
21	DISTRIBUTIONAL LEDGER	Benchmark content favours Western-centric knowledge	—
22	R01 / FIELD-MAP LINKS	LD-06, D4b	—
23	WHAT WOULD CHANGE THIS CLAIM?	Evidence that rankings are stable across culturally balanced subsets	—
24	PUBLICATION STATUS	ELIGIBLE WITH INSTITUTIONAL-POSITION QUALIFIER	state: ELIGIBLE · qualifiers: INSTITUTIONAL_POSITION
25	RECORDED DATE	2026-10-15	—

Field 22 references resolved against Field Map v0.2: LD-06 (LIVING_DEBATE); D4b (SUB_AREA)

The sources as recorded, with their record IDs and coded source types:

Pinned Sources (field 6, version-specific)

“Singh, Romanou, Fourrier, Adelani, Ngui, Vila-Suero et al., “Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation,” arXiv:2412.03304 (v2), 2025” → Singh et al. (2025), “Global MMLU: Understanding and…” (SRC-SL-SINGH-ET-AL-GLOBAL-MMLU-ARXIV-2412-03304--v1.0) — Singh, Romanou, Fourrier, Adelani, Ngui, Vila-Suero et al., “Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation,” arXiv:2412.03304 (v2), 2025; class PREPRINT (explicit public provenance pin)

Cited by Living Debate versions

The evaluation apparatus: Can benchmarks, leaderboards and audits carry the weight placed on them? (v0.1) LD-06

Cite this page

SocioLens project. (2026, October 15). An analysis of MMLU found that 28% of its questions require culturally sensitive knowledge and that 84.9% of its geography questions concern North America or Europe; model rankings change depending on whether the culturally sensitive questions are included, so machine-translated versions distort multilingual comparisons [Claim LD06-SL-C11, version v1.0]. SocioLens. https://sociolens-web.pages.dev/claims/ld06-sl-c11/v1.0/

@misc{sociolens_ld06_sl_c11_v1_0,
  author = {{SocioLens project}},
  title = {An analysis of MMLU found that 28\% of its questions require culturally sensitive knowledge and that 84.9\% of its geography questions concern North America or Europe; model rankings change depending on whether the culturally sensitive questions are included, so machine-translated versions distort multilingual comparisons.},
  year = {2026},
  date = {2026-10-15},
  howpublished = {\url{https://sociolens-web.pages.dev/claims/ld06-sl-c11/v1.0/}},
  note = {Claim LD06-SL-C11, version v1.0}
}

The link points to this version, whose record never changes. For a finding, cite the original study as well: SocioLens summarizes research and does not replace it.

Research-of-record provenance

Materialized by sociolens-materializer 0.6.0 at 2026-09-28T20:00:00.000Z; normalization contract SocioLens — Claim Value Vocabulary v1.0.2 — Pre-Spike Materialization Contract (v1.0.2). Content seal SHA-256 8df269b8f82b90254ab17156b224cc2748f7fd1235eb1d6ff15960cb81066fa2.

Repository-authored inputs (not Drive exports)

SocioLens claim — LD06-SL-C11 v1.0 (v1.0) — written in the SocioLens repository by Project Lead (Claude, AI) on 2026-10-15; no Drive identity exists. Authority: AGENTS.md "Authority" (the Project Lead decides research content within the research-integrity rules) and the Owner's choice in the SocioLens project chat on 15 October 2026 to build the LD-06 debate; a new Claim, first version, written from the project's LD-06 source notes, checked against full texts or official abstracts. Block “ENTRY 11 — LD06-SL-C11” SHA-256 35aa7646005730608728aeabc230d89c2f2784692e6cdbab60665a4ed980ee75; fixture fixtures/authored/claims/LD06-SL-C11--v1.0.

Builder decisions (not Drive data)

VERSION = v1.0 — basis: Claim version taken from the repository-authored claim fixture version (SocioLens claim — LD06-SL-C11 v1.0); the first version of a new Claim of the LD-06 debate
CURRENT_POINTER = true — basis: repository-authored claim "SocioLens claim — LD06-SL-C11 v1.0" (Project Lead (Claude, AI), 2026-10-15); basis: AGENTS.md "Authority" (the Project Lead decides research content within the research-integrity rules) and the Owner's choice in the SocioLens project chat on 15 October 2026 to build the LD-06 debate; a new Claim, first version, written from the project's LD-06 source notes, checked against full texts or official abstracts
FIELD_6_SOURCE_REFERENCE = SRC-SL-SINGH-ET-AL-GLOBAL-MMLU-ARXIV-2412-03304--v1.0 — basis: field 6 of ENTRY 11 — LD06-SL-C11 cites "Singh, Romanou, Fourrier, Adelani, Ngui, Vila-Suero et al., “Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation,” arXiv:2412.03304 (v2), 2025"; the only field-6 segment of this ClaimVersion's repository-authored ledger block.
SOURCE_PROVENANCE_PIN = SRC-SL-SINGH-ET-AL-GLOBAL-MMLU-ARXIV-2412-03304--v1.0 — basis: explicit version-pinned public provenance of this ClaimVersion (Amendment v1.2 §6): the pinned field-6 Source record "Singh, Romanou, Fourrier, Adelani, Ngui, Vila-Suero et al., “Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation,” arXiv:2412.03304 (v2), 2025".