In about 102,000 arXiv AI papers (2014–2024), the share of societally oriented sentences written by computer-science-only teams rose from 49.0% to 71.2%, while the share written by teams including social scientists or humanists fell from 25.7% to 3.8%, although such teams wrote the most societally oriented papers (20.9% of sentences, against 7.8% for computer-science-only teams).

SocioLens project,

Claim LD08-SL-C12 (v1.0)

Research opportunities this claim motivates

What this claim leaves open for research. Each is a hypothesis about a gap, not a finding.

Who writes research on AI's social effects outside arXiv?The rise of computer-science-only teams is measured on arXiv papers only.

Provenance and status

Claim type: Estimate
Publication status: Eligible for publication, with qualifiers: strong scope
Verification state: Checked against the primary source; the source is a preprint. 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: Any statement about research on AI’s social effects published in social-science journals, books or policy reports
Limitations: Read in arXiv version 2 (11 June 2025); no journal version found; the text says interdisciplinary teams are stably about 75% of output while a figure caption says computer-science-only teams are the majority, which this claim does not resolve; teams with social scientists or humanists exclude fully interdisciplinary teams; the classifier read abstract, introduction and conclusion, and many papers lacked one of them; differences hold in a fixed-effects model controlling for year, subfield, team size and length; computational social scientists may be labelled computer science
Source (as cited): Markus, Gilardi & Stetsenko, “Societal AI Research Has Become Less Interdisciplinary,” arXiv:2506.08738, 2025
Source type: Preprint (recorded as “Preprint”)
Institutional position: Independent academic (University of Zurich)
Maturity of the evidence: Emerging evidence
Recorded date: 16 October 2026
Currentness / correction: This is the current version. No correction or concern is recorded on its sources.

Sources this version cites

Markus, Gilardi & Stetsenko, “Societal AI Research Has Become Less Interdisciplinary,” arXiv:2506.08738, 2025 (Preprint)
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 (STRONG_SCOPE) (as printed: “ELIGIBLE WITH STRONG SCOPE QUALIFIER”)
Verification state (coded): CONTENT_VERIFIED_PRIMARY (PREPRINT)
Source type (coded): PREPRINT
Maturity (coded): EMERGING

#	Canonical field	Canonical value (verbatim)	Normalized (Claim Value Vocabulary v1.0.2)
1	CLAIM ID	LD08-SL-C12	—
2	PUBLIC-FACING CLAIM	In about 102,000 arXiv AI papers (2014–2024), the share of societally oriented sentences written by computer-science-only teams rose from 49.0% to 71.2%, while the share written by teams including social scientists or humanists fell from 25.7% to 3.8%, although such teams wrote the most societally oriented papers (20.9% of sentences, against 7.8% for computer-science-only teams).	—
3	CLAIM TYPE	ESTIMATE	base_types: ESTIMATE
4	RESEARCH STRAND	A — Who produces knowledge about AI	—
5	MATURITY	EMERGING	states: EMERGING
6	SOURCE	Markus, Gilardi & Stetsenko, “Societal AI Research Has Become Less Interdisciplinary,” arXiv:2506.08738, 2025	source_ids: SRC-SL-MARKUS-GILARDI-STETSENKO-ARXIV-2506-08738
7	SOURCE TYPE	Preprint	classes: PREPRINT
8	INSTITUTIONAL POSITION	Independent academic (University of Zurich)	—
9	SCOPE	arXiv papers in cs.AI, cs.CV, cs.CL and cs.CY, 2014–2024; social-science journals deliberately excluded	—
10	DESIGN	Authors assigned to disciplines from their prior publications; a sentence classifier for societal orientation applied to introductions and conclusions; research questions extracted with a language model	—
11	SAMPLE / DATASET	101,919 unique papers	—
12	MODEL / TOOL / VERSION	SciBERT-based classifier (F1 0.93); Llama 3.1 8B for research-question extraction	—
13	COMPARATOR	Teams of other compositions	—
14	MAIN RESULT	Computer-science-only share of societal sentences 49.0% (2014) to 71.2% (2024); teams with social scientists or humanists 25.7% to 3.8%; those teams average 20.9% societal sentences against 7.8% for computer-science-only teams	—
15	INFERENTIAL TARGET	Who writes the societally framed parts of technical AI research	—
16	DOES NOT LICENSE	Any statement about research on AI’s social effects published in social-science journals, books or policy reports	—
17	VERIFICATION STATE	CONTENT VERIFIED PREPRINT	state: CONTENT_VERIFIED_PRIMARY · qualifiers: PREPRINT · verified_by: UNKNOWN
18	LIMITATIONS	Read in arXiv version 2 (11 June 2025); no journal version found; the text says interdisciplinary teams are stably about 75% of output while a figure caption says computer-science-only teams are the majority, which this claim does not resolve; teams with social scientists or humanists exclude fully interdisciplinary teams; the classifier read abstract, introduction and conclusion, and many papers lacked one of them; differences hold in a fixed-effects model controlling for year, subfield, team size and length; computational social scientists may be labelled computer science	—
19	CONTRADICTORY / SUPPORTING SOURCES	FAccT is majority STEM: LD08-SL-C13	—
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?	The same measure applied to social-science journals and books, or resolution of the team-share inconsistency	—
24	PUBLICATION STATUS	ELIGIBLE WITH STRONG SCOPE QUALIFIER	state: ELIGIBLE · qualifiers: STRONG_SCOPE
25	RECORDED DATE	2026-10-16	—

Field 22 references resolved against Field Map v0.2: LD-08 (LIVING_DEBATE); D3 (DOMAIN)

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

Pinned Sources (field 6, version-specific)

“Markus, Gilardi & Stetsenko, “Societal AI Research Has Become Less Interdisciplinary,” arXiv:2506.08738, 2025” → Markus et al. (2025), “Societal AI Research Has Become…” (SRC-SL-MARKUS-GILARDI-STETSENKO-ARXIV-2506-08738--v1.0) — Markus, Gilardi & Stetsenko, “Societal AI Research Has Become Less Interdisciplinary,” arXiv:2506.08738, 2025; class PREPRINT (explicit public provenance pin)

Cited by Living Debate versions

Who can know about AI? Epistemic dependence and jurisdiction over the field (v0.1) LD-08

Cite this page

SocioLens project. (2026, October 16). In about 102,000 arXiv AI papers (2014–2024), the share of societally oriented sentences written by computer-science-only teams rose from 49.0% to 71.2%, while the share written by teams including social scientists or humanists fell from 25.7% to 3.8%, although such teams wrote the most societally oriented papers (20.9% of sentences, against 7.8% for computer-science-only teams) [Claim LD08-SL-C12, version v1.0]. SocioLens. https://sociolens-web.pages.dev/claims/ld08-sl-c12/v1.0/

@misc{sociolens_ld08_sl_c12_v1_0,
  author = {{SocioLens project}},
  title = {In about 102,000 arXiv AI papers (2014–2024), the share of societally oriented sentences written by computer-science-only teams rose from 49.0\% to 71.2\%, while the share written by teams including social scientists or humanists fell from 25.7\% to 3.8\%, although such teams wrote the most societally oriented papers (20.9\% of sentences, against 7.8\% for computer-science-only teams).},
  year = {2026},
  date = {2026-10-16},
  howpublished = {\url{https://sociolens-web.pages.dev/claims/ld08-sl-c12/v1.0/}},
  note = {Claim LD08-SL-C12, 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 1b240eabd456b85ef26c0f803b83a034cb44fb7bf467bd7f5ea26d1b85ccdadd.

Repository-authored inputs (not Drive exports)

SocioLens claim — LD08-SL-C12 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 12 — LD08-SL-C12” SHA-256 1dbe99ee9a0d771e1022746c480c2c6b1de2486029ad67ee7e64088f2909cb29; fixture fixtures/authored/claims/LD08-SL-C12--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-C12 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-C12 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-MARKUS-GILARDI-STETSENKO-ARXIV-2506-08738--v1.0 — basis: field 6 of ENTRY 12 — LD08-SL-C12 cites "Markus, Gilardi & Stetsenko, “Societal AI Research Has Become Less Interdisciplinary,” arXiv:2506.08738, 2025"; the only field-6 segment of this ClaimVersion's repository-authored ledger block.
SOURCE_PROVENANCE_PIN = SRC-SL-MARKUS-GILARDI-STETSENKO-ARXIV-2506-08738--v1.0 — basis: explicit version-pinned public provenance of this ClaimVersion (Amendment v1.2 §6): the pinned field-6 Source record "Markus, Gilardi & Stetsenko, “Societal AI Research Has Become Less Interdisciplinary,” arXiv:2506.08738, 2025".