Claim LD08-SL-C07 (v1.0)
Of about 49,800 papers at ten top AI conferences, about one in ten of those published from 2018 to 2022 acknowledged funding from large technology firms; 12% of these reached high citation rates, against 4% of papers with other funding and 2% of unfunded papers, and their reference lists were more insular.
Provenance and status
- Claim type
- ESTIMATE (as printed: “ESTIMATE”)
- Publication status
- ELIGIBLE (PREPRINT) (as printed: “ELIGIBLE WITH PREPRINT QUALIFIER”)
- Verification state
- CONTENT_VERIFIED_PRIMARY (PREPRINT) (as printed: “CONTENT VERIFIED PREPRINT”; verified by: UNKNOWN)
- Does not license
- That industry funding causes higher citation, or anything about research on AI’s social effects
- Source (field 6, as printed)
- Gnewuch, Wahle, Ruas & Gipp, “Big Tech-Funded AI Papers Have Higher Citation Impact, Greater Insularity, and Larger Recency Bias,” arXiv:2512.05714, 2025
- Source type (field 7)
- PREPRINT (as printed: “Preprint”)
- Institutional position
- Independent academic (University of Göttingen)
- Maturity (claim evidence / publication maturity)
- EMERGING (as printed: “EMERGING”)
- Recorded date
- 2026-10-16
- 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--LD08-SL-C07.
Pinned Sources (field 6, version-specific)
- “Gnewuch, Wahle, Ruas & Gipp, “Big Tech-Funded AI Papers Have Higher Citation Impact, Greater Insularity, and Larger Recency Bias,” arXiv:2512.05714, 2025” → SRC-SL-GNEWUCH-ET-AL-ARXIV-2512-05714--v1.0 — Gnewuch, Wahle, Ruas & Gipp, “Big Tech-Funded AI Papers Have Higher Citation Impact, Greater Insularity, and Larger Recency Bias,” arXiv:2512.05714, 2025; class PREPRINT (explicit public provenance pin)
All 25 canonical Claim fields (raw values and normalized values)
| # | Canonical field | Canonical value (verbatim) | Normalized (Claim Value Vocabulary v1.0.2) |
|---|---|---|---|
| 1 | CLAIM ID | LD08-SL-C07 | — |
| 2 | PUBLIC-FACING CLAIM | Of about 49,800 papers at ten top AI conferences, about one in ten of those published from 2018 to 2022 acknowledged funding from large technology firms; 12% of these reached high citation rates, against 4% of papers with other funding and 2% of unfunded papers, and their reference lists were more insular. | — |
| 3 | CLAIM TYPE | ESTIMATE | base_types: ESTIMATE |
| 4 | RESEARCH STRAND | A — Who produces knowledge about AI | — |
| 5 | MATURITY | EMERGING | states: EMERGING |
| 6 | SOURCE | Gnewuch, Wahle, Ruas & Gipp, “Big Tech-Funded AI Papers Have Higher Citation Impact, Greater Insularity, and Larger Recency Bias,” arXiv:2512.05714, 2025 | source_ids: SRC-SL-GNEWUCH-ET-AL-ARXIV-2512-05714 |
| 7 | SOURCE TYPE | Preprint | classes: PREPRINT |
| 8 | INSTITUTIONAL POSITION | Independent academic (University of Göttingen) | — |
| 9 | SCOPE | Ten top AI conferences, 1998–2022, Scopus records | — |
| 10 | DESIGN | Coding of funding acknowledgements; citation analysis | — |
| 11 | SAMPLE / DATASET | About 49,800 papers; about 1.8 million outgoing and 2.3 million incoming citations | — |
| 12 | MODEL / TOOL / VERSION | Not applicable | — |
| 13 | COMPARATOR | Papers with non-industry funding and unfunded papers | — |
| 14 | MAIN RESULT | Industry-funded share below 2% in 2015, 11% in 2020, 9% in 2022; the source gives both 9% and 10% for 2018–2022; high citation rates 12% against 4% and 2% | — |
| 15 | INFERENTIAL TARGET | The scale and citation advantage of industry-funded AI research | — |
| 16 | DOES NOT LICENSE | That industry funding causes higher citation, or anything about research on AI’s social effects | — |
| 17 | VERIFICATION STATE | CONTENT VERIFIED PREPRINT | state: CONTENT_VERIFIED_PRIMARY · qualifiers: PREPRINT · verified_by: UNKNOWN |
| 18 | LIMITATIONS | Read in arXiv version 1; the arXiv record says it was published at an IEEE conference, which was not checked; NeurIPS is not among the ten conferences; funding type explains 13.3% of the variance in citations; funders were coded by one person; acknowledgements under-report funding and miss in-kind compute and model access, as the authors note | — |
| 19 | CONTRADICTORY / SUPPORTING SOURCES | LD08-SL-C05 | — |
| 20 | GEOGRAPHY / LANGUAGE | Global / English | — |
| 21 | DISTRIBUTIONAL LEDGER | Not analysed in this claim | — |
| 22 | R01 / FIELD-MAP LINKS | LD-08, D3 | — |
| 23 | WHAT WOULD CHANGE THIS CLAIM? | Funding data from grant records rather than acknowledgements | — |
| 24 | PUBLICATION STATUS | ELIGIBLE WITH PREPRINT QUALIFIER | state: ELIGIBLE · qualifiers: PREPRINT |
| 25 | RECORDED DATE | 2026-10-16 | — |
Field 22 references resolved against Field Map v0.2: LD-08 (LIVING_DEBATE); D3 (DOMAIN)
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 512cf8fdf1e739d4c9245ac545f4ec0fc05bfdda34ac86c586e55c710df7d859.
Repository-authored inputs (not Drive exports)
- SocioLens claim — LD08-SL-C07 v1.0 (v1.0) — written in the SocioLens repository by Project Lead (Claude, AI) on 2026-10-16; 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 16 October 2026 to build the LD-08 debate; a new Claim, first version, written from the project's LD-08 source notes, checked against full texts, official web pages or official abstracts. Block “ENTRY 07 — LD08-SL-C07” SHA-256
b0beba10d4af67b99eb58e3e7629d299054534b7c779cdc175638b8dde2d996e; fixturefixtures/authored/claims/LD08-SL-C07--v1.0.
Builder decisions (not Drive data)
- VERSION = v1.0 — basis: Claim version taken from the repository-authored claim fixture version (SocioLens claim — LD08-SL-C07 v1.0); the first version of a new Claim of the LD-08 debate
- CURRENT_POINTER = true — basis: repository-authored claim "SocioLens claim — LD08-SL-C07 v1.0" (Project Lead (Claude, AI), 2026-10-16); 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 16 October 2026 to build the LD-08 debate; a new Claim, first version, written from the project's LD-08 source notes, checked against full texts, official web pages or official abstracts
- FIELD_6_SOURCE_REFERENCE = SRC-SL-GNEWUCH-ET-AL-ARXIV-2512-05714--v1.0 — basis: field 6 of ENTRY 07 — LD08-SL-C07 cites "Gnewuch, Wahle, Ruas & Gipp, “Big Tech-Funded AI Papers Have Higher Citation Impact, Greater Insularity, and Larger Recency Bias,” arXiv:2512.05714, 2025"; the only field-6 segment of this ClaimVersion's repository-authored ledger block.
- SOURCE_PROVENANCE_PIN = SRC-SL-GNEWUCH-ET-AL-ARXIV-2512-05714--v1.0 — basis: explicit version-pinned public provenance of this ClaimVersion (Amendment v1.2 §6): the pinned field-6 Source record "Gnewuch, Wahle, Ruas & Gipp, “Big Tech-Funded AI Papers Have Higher Citation Impact, Greater Insularity, and Larger Recency Bias,” arXiv:2512.05714, 2025".