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 page shows version v1.0. Its record never changes, even when newer evidence arrives; the site may add a note to the page or withhold a figure not cleared for public use.

This pinned version is also the current version.

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.