Claim LD02-HQ-C10 (v1.0)
In the US Census 2026 AI supplement, 18% of firms reported using AI in a business function, while only 2% self-reported AI-related employment decreases during the reference period.
Provenance and status
- Claim type
- FACT (SELF_REPORT) (as printed: “FACT (SELF-REPORT)”)
- Publication status
- ELIGIBLE (SELF_REPORT) (as printed: “ELIGIBLE WITH SELF-REPORT QUALIFIER”)
- Verification state
- CONTENT_VERIFIED_PRIMARY (as printed: “CONTENT VERIFIED”; verified by: UNKNOWN)
- Does not license
- Causal aggregate employment effect; “only 2% actually cut jobs”
- Source (field 6, as printed)
- Bonney et al., “The Microstructure of AI Diffusion,” US Census CES-WP-26-25, April 2026
- Source type (field 7)
- WORKING_PAPER (as printed: “Government working paper / nationally representative firm survey”)
- Institutional position
- Government research
- 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--LD02-HQ-C10.
Pinned Sources (field 6, version-specific)
- “Bonney et al., “The Microstructure of AI Diffusion,” US Census CES-WP-26-25, April 2026” → SRC-LD02-BONNEY-CES-26-25--v1.0 — Bonney et al., “The Microstructure of AI Diffusion,” US Census CES-WP-26-25, April 2026; class WORKING_PAPER (explicit public provenance pin)
Read the originals
- SRC-LD02-BONNEY-CES-26-25: open the original
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 | LD02-HQ-C10 | — |
| 2 | PUBLIC-FACING CLAIM | In the US Census 2026 AI supplement, 18% of firms reported using AI in a business function, while only 2% self-reported AI-related employment decreases during the reference period. | — |
| 3 | CLAIM TYPE | FACT (SELF-REPORT) | base_types: FACT · qualifiers: SELF_REPORT |
| 4 | RESEARCH STRAND | A/C — Exposure/adoption/use; firm labour demand | — |
| 5 | MATURITY | RAPIDLY MATURING | states: RAPIDLY_MATURING |
| 6 | SOURCE | Bonney et al., “The Microstructure of AI Diffusion,” US Census CES-WP-26-25, April 2026 | source_ids: SRC-LD02-BONNEY-CES-26-25 |
| 7 | SOURCE TYPE | Government working paper / nationally representative firm survey | classes: WORKING_PAPER |
| 8 | INSTITUTIONAL POSITION | Government research | — |
| 9 | SCOPE | US firms; November 2025–January 2026 | — |
| 10 | DESIGN | Business survey and regression analysis | — |
| 11 | SAMPLE / DATASET | BTOS 2026 AI supplement | — |
| 12 | MODEL / TOOL / VERSION | Broad AI use | — |
| 13 | COMPARATOR | Survey population / users vs non-users | — |
| 14 | MAIN RESULT | 18% firm use, 32% employment-weighted; 23% of firms report worker task use, 41% weighted; 66% of users augment only; 2% report AI-related employment decreases | — |
| 15 | INFERENTIAL TARGET | Adoption/use prevalence and firm-reported employment response | — |
| 16 | DOES NOT LICENSE | Causal aggregate employment effect; “only 2% actually cut jobs” | — |
| 17 | VERIFICATION STATE | CONTENT VERIFIED | state: CONTENT_VERIFIED_PRIMARY · verified_by: UNKNOWN |
| 18 | LIMITATIONS | Self-report; may miss forgone hiring; broad AI | — |
| 19 | CONTRADICTORY / SUPPORTING SOURCES | Yotzov survey; administrative firm studies provide causal complements | — |
| 20 | GEOGRAPHY / LANGUAGE | US / English | — |
| 21 | DISTRIBUTIONAL LEDGER | Adoption concentrated in larger/info/professional/finance firms | — |
| 22 | R01 / FIELD-MAP LINKS | D2, L-C, R-1 | — |
| 23 | WHAT WOULD CHANGE THIS CLAIM? | Later nationally representative waves materially revise prevalence/impact reports | — |
| 24 | PUBLICATION STATUS | ELIGIBLE WITH SELF-REPORT QUALIFIER | state: ELIGIBLE · qualifiers: SELF_REPORT |
| 25 | RECORDED DATE | 2026-09-25 | — |
Field 22 references resolved against Field Map v0.2: D2 (DOMAIN); L-C (LENS); R-1 (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 dabf70db18b229257f524dc8904b77d0534e7b25f2f2ff7a2588214e6274894e.
Frozen Drive-derived inputs
- R05 — LD-02 Canonical Claim Ledger v1.0 — LOCKED (v1.0) — Drive ID
1y7Iid5SaEnjKaPZ7ZsSSVj8dASVlSF8b; revision: NOT_EXPOSED_BY_DRIVE_TEXT_EXPORT; Drive modified ; block “ENTRY 10 — LD02-HQ-C10” SHA-25606e3e33645896d013dec4aac309be888b7237a47de2fef19cc00d0258c82a901; SocioLens — Programme Status & Authority Register v0.6 status “CURRENT.”; frozen fixturefixtures/frozen/r05-ld02-claim-ledger-v1.0-canonical.
Builder decisions (not Drive data)
- VERSION = v1.0 — basis: Claim version taken from the locked R05 canonical ledger v1.0; HQ-ESC-sociolens-ld02-t6-20261011T133040Z-01 ruling 1 authorizes completion of its existing canonical claim corpus. This is the first materialized version of this logical Claim, not a research update.
- CURRENT_POINTER = true — basis: SocioLens — Programme Status & Authority Register v0.6 status for "R05 — LD-02 Canonical Claim Ledger v1.0 — LOCKED": "CURRENT."
- FIELD_6_SOURCE_REFERENCE = SRC-LD02-BONNEY-CES-26-25--v1.0 — basis: field 6 of ENTRY 10 — LD02-HQ-C10 cites "Bonney et al., “The Microstructure of AI Diffusion,” US Census CES-WP-26-25, April 2026"; HQ-ESC-sociolens-ld02-t6-20261011T133040Z-01 ruling 5: this exact frozen field-6 citation segment selects SRC-LD02-BONNEY-CES-26-25--v1.0 under ruling 4; identity established by B1 lines 111–157 and the pinned R05 ledger fields 6/7/8.
- SOURCE_PROVENANCE_PIN = SRC-LD02-BONNEY-CES-26-25--v1.0 — basis: HQ-ESC-sociolens-ld02-t6-20261011T133040Z-01 ruling 5 / Publication System Amendment v1.2 §§4,6: explicit version-pinned public provenance selection of SRC-LD02-BONNEY-CES-26-25--v1.0 for LD02-HQ-C10--v1.0. Preserve the canonical qualification and independently authorized Source metadata.