In Swedish job-ad and register data, the fall in job postings since 2022 tracks monetary tightening rather than AI, but within the same employers, workers aged 22–25 in highly AI-exposed occupations were 5.5% lower by early 2025 than in less-exposed occupations, while workers over 50 were 1.3% higher.

SocioLens project,

Claim LD04-SL-C16 (v1.0)

Provenance and status

Claim type: Estimate
Publication status: Eligible for publication, with qualifiers: working paper, exposure
Verification state: Checked against the abstract of the primary source only. 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: Measured AI use by employers; causal job loss among young workers
Limitations: Working paper; exposure, not use; only the abstract and front matter were read; a related Swedish study (Engberg et al. 2025) finds AI-exposed establishments hired more
Source (as cited): Lodefalk, Löthman, Koch & Engberg, “Same Storm, Different Boats: Generative AI and the Age Gradient in Hiring,” Örebro University Working Paper 2/2026, version of 16 March 2026
Source type: Working paper (recorded as “Academic working paper”)
Institutional position: Independent academic
Maturity of the evidence: Emerging evidence
Recorded date: 14 October 2026
Currentness / correction: This is the current version. No correction or concern is recorded on its sources.

Sources this version cites

Lodefalk, Löthman, Koch & Engberg, “Same Storm, Different Boats: Generative AI and the Age Gradient in Hiring,” Örebro University Working Paper 2/2026, version of 16 March 2026 (Working paper)
No checked link to the original yet.

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

#	Canonical field	Canonical value (verbatim)	Normalized (Claim Value Vocabulary v1.0.2)
1	CLAIM ID	LD04-SL-C16	—
2	PUBLIC-FACING CLAIM	In Swedish job-ad and register data, the fall in job postings since 2022 tracks monetary tightening rather than AI, but within the same employers, workers aged 22–25 in highly AI-exposed occupations were 5.5% lower by early 2025 than in less-exposed occupations, while workers over 50 were 1.3% higher.	—
3	CLAIM TYPE	ESTIMATE	base_types: ESTIMATE
4	RESEARCH STRAND	C — Entry, apprenticeship and returns to experience	—
5	MATURITY	EMERGING	states: EMERGING
6	SOURCE	Lodefalk, Löthman, Koch & Engberg, “Same Storm, Different Boats: Generative AI and the Age Gradient in Hiring,” Örebro University Working Paper 2/2026, version of 16 March 2026	source_ids: SRC-SL-LODEFALK-LOTHMAN-KOCH-ENGBERG-ORU-WP-2-2026
7	SOURCE TYPE	Academic working paper	classes: WORKING_PAPER
8	INSTITUTIONAL POSITION	Independent academic	—
9	SCOPE	Sweden; job ads from the largest recruitment platform and full-population employer–employee registers	—
10	DESIGN	Employer-level difference-in-differences across six age groups; timing test using the gap between the first Riksbank rate rise and ChatGPT’s release	—
11	SAMPLE / DATASET	4.6 million job ads; population registers	—
12	MODEL / TOOL / VERSION	Occupational AI exposure	—
13	COMPARATOR	Less-exposed occupations within the same employers	—
14	MAIN RESULT	Posting decline tracks monetary tightening; 22–25-year-olds in high-exposure occupations 5.5% lower by early 2025; over-50s +1.3%; no fall in aggregate labour demand	—
15	INFERENTIAL TARGET	Age gradient in employment by occupational AI exposure	—
16	DOES NOT LICENSE	Measured AI use by employers; causal job loss among young workers	—
17	VERIFICATION STATE	CONTENT VERIFIED ABSTRACT	state: CONTENT_VERIFIED_PRIMARY · qualifiers: ABSTRACT_ONLY · verified_by: UNKNOWN
18	LIMITATIONS	Working paper; exposure, not use; only the abstract and front matter were read; a related Swedish study (Engberg et al. 2025) finds AI-exposed establishments hired more	—
19	CONTRADICTORY / SUPPORTING SOURCES	Non-US corroboration of a young-worker gap in exposed occupations; contrasts with Norwegian near-zero differences (LD-02)	—
20	GEOGRAPHY / LANGUAGE	Sweden / Not checked	—
21	DISTRIBUTIONAL LEDGER	Young workers in exposed occupations lose relative to older workers	—
22	R01 / FIELD-MAP LINKS	LD-04, LD-02, D2	—
23	WHAT WOULD CHANGE THIS CLAIM?	Firm-level AI-use data, or later data in which the age gap closes	—
24	PUBLICATION STATUS	ELIGIBLE WITH WORKING-PAPER / EXPOSURE QUALIFIER	state: ELIGIBLE · qualifiers: WORKING_PAPER, EXPOSURE
25	RECORDED DATE	2026-10-14	—

Field 22 references resolved against Field Map v0.2: LD-04 (LIVING_DEBATE); LD-02 (LIVING_DEBATE); D2 (DOMAIN)

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

Pinned Sources (field 6, version-specific)

“Lodefalk, Löthman, Koch & Engberg, “Same Storm, Different Boats: Generative AI and the Age Gradient in Hiring,” Örebro University Working Paper 2/2026, version of 16 March 2026” → Lodefalk et al. (2026), “Same Storm, Different Boats…” (SRC-SL-LODEFALK-LOTHMAN-KOCH-ENGBERG-ORU-WP-2-2026--v1.0) — Lodefalk, Löthman, Koch & Engberg, “Same Storm, Different Boats: Generative AI and the Age Gradient in Hiring,” Örebro University Working Paper 2/2026, version of 16 March 2026; class WORKING_PAPER (explicit public provenance pin)

Cited by Living Debate versions

Cite this page

SocioLens project. (2026, October 14). In Swedish job-ad and register data, the fall in job postings since 2022 tracks monetary tightening rather than AI, but within the same employers, workers aged 22–25 in highly AI-exposed occupations were 5.5% lower by early 2025 than in less-exposed occupations, while workers over 50 were 1.3% higher [Claim LD04-SL-C16, version v1.0]. SocioLens. https://sociolens-web.pages.dev/claims/ld04-sl-c16/v1.0/

@misc{sociolens_ld04_sl_c16_v1_0,
  author = {{SocioLens project}},
  title = {In Swedish job-ad and register data, the fall in job postings since 2022 tracks monetary tightening rather than AI, but within the same employers, workers aged 22–25 in highly AI-exposed occupations were 5.5\% lower by early 2025 than in less-exposed occupations, while workers over 50 were 1.3\% higher.},
  year = {2026},
  date = {2026-10-14},
  howpublished = {\url{https://sociolens-web.pages.dev/claims/ld04-sl-c16/v1.0/}},
  note = {Claim LD04-SL-C16, 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 495d779961601b137a72da1bd445c889a2b795f68508b33a9b1c022b1aa9cd29.

Repository-authored inputs (not Drive exports)

SocioLens claim — LD04-SL-C16 v1.0 (v1.0) — written in the SocioLens repository by Project Lead (Claude, AI) on 2026-10-14; 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 14 October 2026 to build the LD-04 debate; a new Claim, first version, written from the project's LD-04 source notes, checked against full texts or official abstracts. Block “ENTRY 16 — LD04-SL-C16” SHA-256 30bc7c7c1966148d2cc56e89ea19b6b1f7035135728751a4f844258588825fa3; fixture fixtures/authored/claims/LD04-SL-C16--v1.0.

Builder decisions (not Drive data)

VERSION = v1.0 — basis: Claim version taken from the repository-authored claim fixture version (SocioLens claim — LD04-SL-C16 v1.0); the first version of a new Claim of the LD-04 debate
CURRENT_POINTER = true — basis: repository-authored claim "SocioLens claim — LD04-SL-C16 v1.0" (Project Lead (Claude, AI), 2026-10-14); 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 14 October 2026 to build the LD-04 debate; a new Claim, first version, written from the project's LD-04 source notes, checked against full texts or official abstracts
FIELD_6_SOURCE_REFERENCE = SRC-SL-LODEFALK-LOTHMAN-KOCH-ENGBERG-ORU-WP-2-2026--v1.0 — basis: field 6 of ENTRY 16 — LD04-SL-C16 cites "Lodefalk, Löthman, Koch & Engberg, “Same Storm, Different Boats: Generative AI and the Age Gradient in Hiring,” Örebro University Working Paper 2/2026, version of 16 March 2026"; the only field-6 segment of this ClaimVersion's repository-authored ledger block.
SOURCE_PROVENANCE_PIN = SRC-SL-LODEFALK-LOTHMAN-KOCH-ENGBERG-ORU-WP-2-2026--v1.0 — basis: explicit version-pinned public provenance of this ClaimVersion (Amendment v1.2 §6): the pinned field-6 Source record "Lodefalk, Löthman, Koch & Engberg, “Same Storm, Different Boats: Generative AI and the Age Gradient in Hiring,” Örebro University Working Paper 2/2026, version of 16 March 2026".