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Claim LD10-HQ-C23 (v1.1)

China-originating LLMs showed higher refusal rates, shorter responses and more inaccurate answers on 145 China-politics questions than non-China models; the study is observational and does not establish that regulation causes the gap.

Provenance and status

Claim type
Estimate
Publication status
Eligible for publication, with qualifiers: non causal
Verification state
Checked against the primary source. 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
Causal regulatory effect or downstream belief effect
Limitations
Observational; model vintages; provider and technical differences
Source (as cited)
Pan & Xu, PNAS Nexus 2026
Source type
Peer-reviewed journal article (recorded as “Peer-reviewed article”)
Institutional position
Independent academic
Maturity of the evidence
Emerging evidence
Recorded date
13 October 2026
Currentness / correction
This is the current version. No correction or concern is recorded on its sources.

Sources this version cites

Version

This is the current version, v1.1. Earlier versions stay available, and their records never change.

Versions: v1.0, v1.1 · current

What changed in this version

This version supersedes version v1.0 (LD10-HQ-C23--v1.0), which stays available with its record unchanged.

Changed fields
2 PUBLIC-FACING CLAIM; 25 RECORDED DATE
What changed
The public-facing claim now says the study does not establish that regulation causes the gap, instead of saying it does not identify regulation as the "sole" cause.
Why
A claim check on 13 October 2026 found that "not the sole cause" implies the study shows regulation to be a partial cause; the HQ primary read of Pan & Xu says the study explicitly does not establish a causal relationship between regulation and censorship behaviour. The check and this revision were done by AI agents against the HQ notes, not by a person.
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 (NON_CAUSAL) (as printed: “ELIGIBLE WITH NON-CAUSAL QUALIFIER”)
Verification state (coded)
CONTENT_VERIFIED_PRIMARY
Source type (coded)
PEER_REVIEWED_JOURNAL_ARTICLE
Maturity (coded)
EMERGING
#Canonical fieldCanonical value (verbatim)Normalized (Claim Value Vocabulary v1.0.2)
1CLAIM IDLD10-HQ-C23—
2PUBLIC-FACING CLAIMChina-originating LLMs showed higher refusal rates, shorter responses and more inaccurate answers on 145 China-politics questions than non-China models; the study is observational and does not establish that regulation causes the gap.—
3CLAIM TYPEESTIMATEbase_types: ESTIMATE
4RESEARCH STRANDF — Platform/jurisdiction governance—
5MATURITYEMERGINGstates: EMERGING
6SOURCEPan & Xu, PNAS Nexus 2026source_ids: SRC-LD07-PAN-XU-CENSORSHIP-2026
7SOURCE TYPEPeer-reviewed articleclasses: PEER_REVIEWED_JOURNAL_ARTICLE
8INSTITUTIONAL POSITIONIndependent academic—
9SCOPEChinese- and English-language prompts; China-origin vs non-China models—
10DESIGNCross-sectional audit—
11SAMPLE / DATASET145 political questions plus less-sensitive set—
12MODEL / TOOL / VERSIONBaiChuan, ChatGLM, Ernie, DeepSeek vs Llama/GPT families—
13COMPARATORChina-origin vs non-China-origin models—
14MAIN RESULTLarge refusal/content differences; smaller gaps on less-sensitive prompts; all models refused more in Chinese—
15INFERENTIAL TARGETAssociation between provider origin/jurisdiction and model behaviour—
16DOES NOT LICENSECausal regulatory effect or downstream belief effect—
17VERIFICATION STATECONTENT VERIFIEDstate: CONTENT_VERIFIED_PRIMARY · verified_by: UNKNOWN
18LIMITATIONSObservational; model vintages; provider and technical differences—
19CONTRADICTORY / SUPPORTING SOURCESChinese regulatory framework is a plausible institutional condition—
20GEOGRAPHY / LANGUAGEPRC-origin vs non-PRC / Chinese and English—
21DISTRIBUTIONAL LEDGERChinese-language users received more refusals across models—
22R01 / FIELD-MAP LINKSD7, D6, D9, L-B, R-1—
23WHAT WOULD CHANGE THIS CLAIM?Newer-model longitudinal audit or causal design—
24PUBLICATION STATUSELIGIBLE WITH NON-CAUSAL QUALIFIERstate: ELIGIBLE · qualifiers: NON_CAUSAL
25RECORDED DATE2026-10-13—

Field 22 references resolved against Field Map v0.2: D7 (DOMAIN); D6 (DOMAIN); D9 (DOMAIN); L-B (LENS); R-1 (LENS)

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

Pinned Sources (field 6, version-specific)

  • “Pan & Xu, PNAS Nexus 2026” → Pan & Xu (2026), “Political censorship in large language…” (SRC-LD07-PAN-XU-CENSORSHIP-2026--v1.0) — Pan & Xu, “Political censorship in large language models originating from China,” PNAS Nexus 5(2):pgag013 (2026); class PEER_REVIEWED_JOURNAL_ARTICLE (explicit public provenance pin)
Cite this page

SocioLens project. (2026, October 13). China-originating LLMs showed higher refusal rates, shorter responses and more inaccurate answers on 145 China-politics questions than non-China models; the study is observational and does not establish that regulation causes the gap [Claim LD10-HQ-C23, version v1.1]. SocioLens. https://sociolens-web.pages.dev/claims/ld10-hq-c23/v1.1/

@misc{sociolens_ld10_hq_c23_v1_1,
  author = {{SocioLens project}},
  title = {China-originating LLMs showed higher refusal rates, shorter responses and more inaccurate answers on 145 China-politics questions than non-China models; the study is observational and does not establish that regulation causes the gap.},
  year = {2026},
  date = {2026-10-13},
  howpublished = {\url{https://sociolens-web.pages.dev/claims/ld10-hq-c23/v1.1/}},
  note = {Claim LD10-HQ-C23, version v1.1}
}

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 42999ace40b1a0e064cbb5db742a1d6b8f14c5bcb7e542adeb96c85cf115b0d1.

Repository-authored inputs (not Drive exports)

  • SocioLens claim revision — LD10-HQ-C23 v1.1 (v1.1) — written in the SocioLens repository by Project Lead (Claude, AI) on 2026-10-13; no Drive identity exists. Authority: AGENTS.md "Authority" (the Project Lead decides research content within the research-integrity rules) and docs/PROJECT.md "Research revisions" (a published claim changes only through a new version that states what changed and why). Block “ENTRY 23 — LD10-HQ-C23” SHA-256 b43928015cbcfda8409c2381df0b1f843facf02602e2c8540da96acbd2196f81; fixture fixtures/authored/claim-revisions/LD10-HQ-C23--v1.1.

Builder decisions (not Drive data)

  • VERSION = v1.1 — basis: Claim version taken from the repository-authored revision fixture version (SocioLens claim revision — LD10-HQ-C23 v1.1); a new version of LD10-HQ-C23 v1.0, which stays routable (AGENTS.md research integrity rule 3)
  • CURRENT_POINTER = true — basis: repository-authored revision "SocioLens claim revision — LD10-HQ-C23 v1.1" (Project Lead (Claude, AI), 2026-10-13); basis: AGENTS.md "Authority" (the Project Lead decides research content within the research-integrity rules) and docs/PROJECT.md "Research revisions" (a published claim changes only through a new version that states what changed and why)
  • FIELD_6_SOURCE_REFERENCE = SRC-LD07-PAN-XU-CENSORSHIP-2026--v1.0 — basis: field 6 of ENTRY 23 — LD10-HQ-C23 cites "Pan & Xu, PNAS Nexus 2026"; the first field-6 segment of this ClaimVersion's repository-authored ledger block; the same Source record LD10-HQ-C23 v1.0 cites.
  • SOURCE_PROVENANCE_PIN = SRC-LD07-PAN-XU-CENSORSHIP-2026--v1.0 — basis: explicit version-pinned public provenance of this ClaimVersion (Amendment v1.2 §6): the pinned field-6 Source record "Pan & Xu, PNAS Nexus 2026".