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Claim LD07-HQ-C16 (v1.0)

In a conditionally accepted AJPS manuscript re-running 14 published political-science annotation pipelines, substituting LLM-generated labels changed the substantive statistical conclusion in approximately 35–42% of estimates across the tested prompt/in-context-learning settings.

Provenance and status

Claim type
ESTIMATE (as printed: “ESTIMATE”)
Publication status
ELIGIBLE (CONDITIONAL_ACCEPTANCE, CORPUS) (as printed: “ELIGIBLE WITH CONDITIONAL-ACCEPTANCE / CORPUS QUALIFIER”)
Verification state
CONTENT_VERIFIED_PRIMARY (SOURCE_SPECIFIC) (as printed: “CLEARED WITH QUALIFIER”; verified by: UNKNOWN)
Does not license
Claim that 35–42% of political-science findings are wrong; claim that fresh experts would agree with original labels; generalization beyond the selected 14-study corpus
Source (field 6, as printed)
Eddie Yang, Zoey Wang, Carl Zhou, Yaosheng Xu, “Data Annotation with Large Language Models: Lessons from a Large Empirical Evaluation”
Source type (field 7)
WORKING_PAPER (as printed: “Conditionally accepted journal manuscript / current pre-publication PDF”)
Institutional position
Independent academic
Maturity (claim evidence / publication maturity)
RAPIDLY_MATURING (as printed: “RAPIDLY MATURING”)
Recorded date
2026-09-25
Currentness / correction
This is the current version. No correction or concern relation is recorded on its Sources.

Version

Current version v1.0, resolved through the explicit current pointer CLAIM--LD07-HQ-C16.

Versions:v1.0 · current

Pinned Sources (field 6, version-specific)

Read the originals

All 25 canonical Claim fields (raw values and normalized values)
#Canonical fieldCanonical value (verbatim)Normalized (Claim Value Vocabulary v1.0.2)
1CLAIM IDLD07-HQ-C16—
2PUBLIC-FACING CLAIMIn a conditionally accepted AJPS manuscript re-running 14 published political-science annotation pipelines, substituting LLM-generated labels changed the substantive statistical conclusion in approximately 35–42% of estimates across the tested prompt/in-context-learning settings.—
3CLAIM TYPEESTIMATEbase_types: ESTIMATE
4RESEARCH STRANDA — Annotation/coding/classification—
5MATURITYRAPIDLY MATURINGstates: RAPIDLY_MATURING
6SOURCEEddie Yang, Zoey Wang, Carl Zhou, Yaosheng Xu, “Data Annotation with Large Language Models: Lessons from a Large Empirical Evaluation”source_ids: SRC-LD07-YANG-DATA-ANNOTATION-EVALUATION
7SOURCE TYPEConditionally accepted journal manuscript / current pre-publication PDFclasses: WORKING_PAPER
8INSTITUTIONAL POSITIONIndependent academic—
9SCOPE14 political-science studies published 2018–2025 in leading journals, using discrete annotations in downstream statistical inference—
10DESIGNMulti-study re-annotation and downstream re-estimation—
11SAMPLE / DATASETMore than three million original annotations across included studies; exact generated-annotation total version-sensitive—
12MODEL / TOOL / VERSIONMultiple contemporary LLMs; current manuscript contains an internal 15/16-model-count inconsistency, so no exact count is public-canonical—
13COMPARATOROriginal study labels and original published statistical conclusions—
14MAIN RESULTLLM-derived estimates changed the substantive statistical conclusion in approximately 35–42% of cases across tested configurations; LLM-pair disagreement also produced sign/significance differences—
15INFERENTIAL TARGETPreservation of original published downstream conclusions when labels are substituted—
16DOES NOT LICENSEClaim that 35–42% of political-science findings are wrong; claim that fresh experts would agree with original labels; generalization beyond the selected 14-study corpus—
17VERIFICATION STATECLEARED WITH QUALIFIERstate: CONTENT_VERIFIED_PRIMARY · qualifiers: SOURCE_SPECIFIC · verified_by: UNKNOWN
18LIMITATIONSConditionally accepted, not yet version-of-record; selected corpus; exact model count internally inconsistent in current PDF—
19CONTRADICTORY / SUPPORTING SOURCESBaumann independently supports the downstream-failure class; Nakamura shows narrow fresh-expert equivalence under a different estimand—
20GEOGRAPHY / LANGUAGEPolitical-science text tasks, primarily English—
21DISTRIBUTIONAL LEDGERNo broad subgroup-validity guarantee—
22R01 / FIELD-MAP LINKSD9, R-1, R-2—
23WHAT WOULD CHANGE THIS CLAIM?Frozen accepted/VOR manuscript materially revising the 35–42% result, or independent exact replication showing substantially greater preservation—
24PUBLICATION STATUSELIGIBLE WITH CONDITIONAL-ACCEPTANCE / CORPUS QUALIFIERstate: ELIGIBLE · qualifiers: CONDITIONAL_ACCEPTANCE, CORPUS
25RECORDED DATE2026-09-25—

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

Cited by Living Debate versions

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 869c683f6541617c3647cd82026b337aa7c3c2ff63679feb49e500adbd949a02.

Frozen Drive-derived inputs

  • R03 — LD-07 Canonical Claim Ledger v1.0 — LOCKED (v1.0) — Drive ID 1xVz_LrQAA8EA1tPhVWIrDgOUU3Zidlg9; revision: NOT_EXPOSED_BY_DRIVE_TEXT_EXPORT; Drive modified 2026-09-29T04:31:14.120Z; block “ENTRY 16 — LD07-HQ-C16” SHA-256 70c22940247ca3b84bece80284654946b4e89ca05011a100f63ce85e0bfc2fd7; SocioLens — Programme Status & Authority Register v0.6 status “CURRENT.”; frozen fixture fixtures/frozen/r03-ld07-claim-ledger-v1.0-canonical.

Builder decisions (not Drive data)

  • VERSION = v1.0 — basis: Claim version taken from the canonical ledger artifact version (R03 — LD-07 Canonical Claim Ledger v1.0); Implementation Architecture Selection §5
  • CURRENT_POINTER = true — basis: SocioLens — Programme Status & Authority Register v0.6 status for "R03 — LD-07 Canonical Claim Ledger v1.0 — LOCKED": "CURRENT."
  • FIELD_17_CONTEXT_QUALIFIERS = SOURCE_SPECIFIC — basis: R03 — LD-07 Canonical Claim Ledger v1.0 — LOCKED (v1.0, Drive 1xVz_LrQAA8EA1tPhVWIrDgOUU3Zidlg9)
  • FIELD_6_SOURCE_REFERENCE = SRC-LD07-YANG-DATA-ANNOTATION-EVALUATION--v1.0 — basis: field 6 of ENTRY 16 — LD07-HQ-C16 cites "Eddie Yang, Zoey Wang, Carl Zhou, Yaosheng Xu, “Data Annotation with Large Language Models: Lessons from a Large Empirical Evaluation”"; the frozen field-6 segment of this ClaimVersion's ledger block; Drive-derived identity authority (Issue #39 Source inventory): Batch 01 §3; ledger C16 fields 6/7/8; KEY EVIDENCE.
  • SOURCE_PROVENANCE_PIN = SRC-LD07-YANG-DATA-ANNOTATION-EVALUATION--v1.0 — basis: Issue #5 proof rendering (Architecture Proof Protocol v0.1 AP-08 / Amendment v1.2 §6): explicit version-pinned public provenance of this ClaimVersion — the pinned field-6 Source record "Eddie Yang, Zoey Wang, Carl Zhou, Yaosheng Xu, “Data Annotation with Large Language Models: Lessons from a Large Empirical Evaluation”"; Drive-derived identity authority (Issue #39 Source inventory): Batch 01 §3; ledger C16 fields 6/7/8; KEY EVIDENCE.