In a UK exposure-based working paper, highly LLM-exposed firms experienced about 4.5% lower employment, junior employment about 5.8% lower, and highly exposed occupations about 23.4% fewer job postings over the study period.

SocioLens project,

Claim LD02-HQ-C08 (v1.0)

Provenance and status

Claim type: Estimate
Publication status: Eligible for publication, with qualifiers: exposure, working paper
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: Observed-adoption effect; national aggregate decline; direct layoff estimate
Limitations: Exposure not use; working paper; postings differ from employment; period ends 2025
Source (as cited): Klein Teeselink, “Generative AI and Labor Market Outcomes: Evidence from the United Kingdom,” SSRN, revised December 2025
Source type: Working paper (recorded as “Academic working paper”)
Institutional position: Independent academic
Maturity of the evidence: Emerging evidence
Recorded date: 25 September 2026
Currentness / correction: This is the current version. No correction or concern is recorded on its sources.

Sources this version cites

Klein Teeselink, “Generative AI and Labor Market Outcomes: Evidence from the United Kingdom,” SSRN, revised December 2025 (Working paper)
Read the original

Version

This is the current version, v1.0. Earlier versions stay available, and their records never change.

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 (EXPOSURE, WORKING_PAPER) (as printed: “ELIGIBLE WITH EXPOSURE / WORKING-PAPER QUALIFIER”)
Verification state (coded): CONTENT_VERIFIED_PRIMARY
Source type (coded): WORKING_PAPER
Maturity (coded): EMERGING

#	Canonical field	Canonical value (verbatim)	Normalized (Claim Value Vocabulary v1.0.2)
1	CLAIM ID	LD02-HQ-C08	—
2	PUBLIC-FACING CLAIM	In a UK exposure-based working paper, highly LLM-exposed firms experienced about 4.5% lower employment, junior employment about 5.8% lower, and highly exposed occupations about 23.4% fewer job postings over the study period.	—
3	CLAIM TYPE	ESTIMATE	base_types: ESTIMATE
4	RESEARCH STRAND	D — Hiring, entry and career ladders	—
5	MATURITY	EMERGING	states: EMERGING
6	SOURCE	Klein Teeselink, “Generative AI and Labor Market Outcomes: Evidence from the United Kingdom,” SSRN, revised December 2025	source_ids: SRC-LD02-KLEIN-TEESELINK-UK-2025
7	SOURCE TYPE	Academic working paper	classes: WORKING_PAPER
8	INSTITUTIONAL POSITION	Independent academic	—
9	SCOPE	UK firms and occupations, 2021–2025	—
10	DESIGN	Difference-in-differences by LLM exposure	—
11	SAMPLE / DATASET	Revelio / LinkedIn-style labour-market data as specified by paper	—
12	MODEL / TOOL / VERSION	LLM capability exposure index	—
13	COMPARATOR	Less-exposed firms / occupations	—
14	MAIN RESULT	Employment −4.5%; junior employment −5.8%; exposed occupation postings −23.4%	—
15	INFERENTIAL TARGET	Exposure-linked firm and vacancy contraction	—
16	DOES NOT LICENSE	Observed-adoption effect; national aggregate decline; direct layoff estimate	—
17	VERIFICATION STATE	CONTENT VERIFIED	state: CONTENT_VERIFIED_PRIMARY · verified_by: UNKNOWN
18	LIMITATIONS	Exposure not use; working paper; postings differ from employment; period ends 2025	—
19	CONTRADICTORY / SUPPORTING SOURCES	Supports US entry signal; multinational affiliate study differs in mechanism	—
20	GEOGRAPHY / LANGUAGE	UK / English	—
21	DISTRIBUTIONAL LEDGER	Junior and high-wage/high-exposure segments more affected	—
22	R01 / FIELD-MAP LINKS	D2, D4b, L-A, L-B	—
23	WHAT WOULD CHANGE THIS CLAIM?	Later UK administrative data fail to reproduce exposure-linked reductions	—
24	PUBLICATION STATUS	ELIGIBLE WITH EXPOSURE / WORKING-PAPER QUALIFIER	state: ELIGIBLE · qualifiers: EXPOSURE, WORKING_PAPER
25	RECORDED DATE	2026-09-25	—

Field 22 references resolved against Field Map v0.2: D2 (DOMAIN); D4b (SUB_AREA); L-A (LENS); L-B (LENS)

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

Pinned Sources (field 6, version-specific)

“Klein Teeselink, “Generative AI and Labor Market Outcomes: Evidence from the United Kingdom,” SSRN, revised December 2025” → Klein Teeselink (2025), “Generative AI and Labor Market…” (SRC-LD02-KLEIN-TEESELINK-UK-2025--v1.0) — Klein Teeselink, “Generative AI and Labor Market Outcomes: Evidence from the United Kingdom,” SSRN, revised December 2025; class WORKING_PAPER (explicit public provenance pin)

Cited by Living Debate versions

Cite this page

SocioLens project. (2026, September 25). In a UK exposure-based working paper, highly LLM-exposed firms experienced about 4.5% lower employment, junior employment about 5.8% lower, and highly exposed occupations about 23.4% fewer job postings over the study period [Claim LD02-HQ-C08, version v1.0]. SocioLens. https://sociolens-web.pages.dev/claims/ld02-hq-c08/v1.0/

@misc{sociolens_ld02_hq_c08_v1_0,
  author = {{SocioLens project}},
  title = {In a UK exposure-based working paper, highly LLM-exposed firms experienced about 4.5\% lower employment, junior employment about 5.8\% lower, and highly exposed occupations about 23.4\% fewer job postings over the study period.},
  year = {2026},
  date = {2026-09-25},
  howpublished = {\url{https://sociolens-web.pages.dev/claims/ld02-hq-c08/v1.0/}},
  note = {Claim LD02-HQ-C08, 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 d4d5702633170090ad62d2d986336ec02a87f4401596856bfbdc7be18237e292.

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 08 — LD02-HQ-C08” SHA-256 c20e1075595e0dbea57cb5afac20da48fd6d38d96c687d4c0013c83e88db0cee; SocioLens — Programme Status & Authority Register v0.6 status “CURRENT.”; frozen fixture fixtures/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-KLEIN-TEESELINK-UK-2025--v1.0 — basis: field 6 of ENTRY 08 — LD02-HQ-C08 cites "Klein Teeselink, “Generative AI and Labor Market Outcomes: Evidence from the United Kingdom,” SSRN, revised December 2025"; HQ-ESC-sociolens-ld02-t6-20261011T133040Z-01 ruling 5: this exact frozen field-6 citation segment selects SRC-LD02-KLEIN-TEESELINK-UK-2025--v1.0 under ruling 4; identity established by B2 lines 201–243 and the pinned R05 ledger fields 6/7/8.
SOURCE_PROVENANCE_PIN = SRC-LD02-KLEIN-TEESELINK-UK-2025--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-KLEIN-TEESELINK-UK-2025--v1.0 for LD02-HQ-C08--v1.0. Preserve the canonical qualification and independently authorized Source metadata.