In argumentative essays co-written with a language model, only the instruction-tuned model (InstructGPT) made essays more alike; the base model (GPT-3) did not, and the reduction in diversity came from the text the model contributed, while the users’ own text remained unaffected.

SocioLens project,

Claim LD09-SL-C14 (v1.0)

Provenance and status

Claim type: Estimate
Publication status: Eligible for publication, with a qualifier
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: Effects of current models, or on essay quality
Limitations: Small corpus; one genre; models from 2022; read in the arXiv version 3 (July 2024), posted after the ICLR 2024 acceptance; the proceedings version was not read
Source (as cited): Padmakumar & He, “Does Writing with Language Models Reduce Content Diversity?,” ICLR 2024, arXiv:2309.05196
Source type: Peer-reviewed conference paper (recorded as “Peer-reviewed conference paper”)
Institutional position: Independent academic (New York University)
Maturity of the evidence: Emerging evidence
Recorded date: 15 October 2026
Currentness / correction: This is the current version. No correction or concern is recorded on its sources.

Sources this version cites

Padmakumar & He, “Does Writing with Language Models Reduce Content Diversity?,” ICLR 2024, arXiv:2309.05196 (Peer-reviewed conference 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 (QUALIFIED) (as printed: “ELIGIBLE WITH QUALIFIER”)
Verification state (coded): CONTENT_VERIFIED_PRIMARY
Source type (coded): PEER_REVIEWED_CONFERENCE_PAPER
Maturity (coded): EMERGING

#	Canonical field	Canonical value (verbatim)	Normalized (Claim Value Vocabulary v1.0.2)
1	CLAIM ID	LD09-SL-C14	—
2	PUBLIC-FACING CLAIM	In argumentative essays co-written with a language model, only the instruction-tuned model (InstructGPT) made essays more alike; the base model (GPT-3) did not, and the reduction in diversity came from the text the model contributed, while the users’ own text remained unaffected.	—
3	CLAIM TYPE	ESTIMATE	base_types: ESTIMATE
4	RESEARCH STRAND	B — Creative work, writing and ideas	—
5	MATURITY	EMERGING	states: EMERGING
6	SOURCE	Padmakumar & He, “Does Writing with Language Models Reduce Content Diversity?,” ICLR 2024, arXiv:2309.05196	source_ids: SRC-SL-PADMAKUMAR-HE-ICLR-2024
7	SOURCE TYPE	Peer-reviewed conference paper	classes: PEER_REVIEWED_CONFERENCE_PAPER
8	INSTITUTIONAL POSITION	Independent academic (New York University)	—
9	SCOPE	Argumentative essays on ten topics	—
10	DESIGN	Controlled writing study with three setups (solo, base model, instruction-tuned model)	—
11	SAMPLE / DATASET	300 essays by paid native English-speaking writers	—
12	MODEL / TOOL / VERSION	GPT-3 (davinci) and InstructGPT (2022)	—
13	COMPARATOR	Essays written alone	—
14	MAIN RESULT	Key-point homogenization (Rouge-L): solo 0.1536, GPT-3 0.1578, InstructGPT 0.1660, with only InstructGPT significantly different; lexical and key-point diversity also lower with InstructGPT; user-written text unaffected	—
15	INFERENTIAL TARGET	Where in human–AI writing homogenization comes from	—
16	DOES NOT LICENSE	Effects of current models, or on essay quality	—
17	VERIFICATION STATE	CONTENT VERIFIED	state: CONTENT_VERIFIED_PRIMARY · verified_by: UNKNOWN
18	LIMITATIONS	Small corpus; one genre; models from 2022; read in the arXiv version 3 (July 2024), posted after the ICLR 2024 acceptance; the proceedings version was not read	—
19	CONTRADICTORY / SUPPORTING SOURCES	Not applicable	—
20	GEOGRAPHY / LANGUAGE	Not checked / English	—
21	DISTRIBUTIONAL LEDGER	Not recorded	—
22	R01 / FIELD-MAP LINKS	LD-09, D3	—
23	WHAT WOULD CHANGE THIS CLAIM?	Replication with current models and tuning methods	—
24	PUBLICATION STATUS	ELIGIBLE WITH QUALIFIER	state: ELIGIBLE · qualifiers: QUALIFIED
25	RECORDED DATE	2026-10-15	—

Field 22 references resolved against Field Map v0.2: LD-09 (LIVING_DEBATE); D3 (DOMAIN)

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

Pinned Sources (field 6, version-specific)

“Padmakumar & He, “Does Writing with Language Models Reduce Content Diversity?,” ICLR 2024, arXiv:2309.05196” → Padmakumar & He (2024), “Does Writing with Language…” (SRC-SL-PADMAKUMAR-HE-ICLR-2024--v1.0) — Padmakumar & He, “Does Writing with Language Models Reduce Content Diversity?,” ICLR 2024, arXiv:2309.05196; class PEER_REVIEWED_CONFERENCE_PAPER (explicit public provenance pin)

Cited by Living Debate versions

Individual gain, collective narrowing? Does AI make science, creative work and shared knowledge more alike? (v0.1) LD-09

Cite this page

SocioLens project. (2026, October 15). In argumentative essays co-written with a language model, only the instruction-tuned model (InstructGPT) made essays more alike; the base model (GPT-3) did not, and the reduction in diversity came from the text the model contributed, while the users’ own text remained unaffected [Claim LD09-SL-C14, version v1.0]. SocioLens. https://sociolens-web.pages.dev/claims/ld09-sl-c14/v1.0/

@misc{sociolens_ld09_sl_c14_v1_0,
  author = {{SocioLens project}},
  title = {In argumentative essays co-written with a language model, only the instruction-tuned model (InstructGPT) made essays more alike; the base model (GPT-3) did not, and the reduction in diversity came from the text the model contributed, while the users’ own text remained unaffected.},
  year = {2026},
  date = {2026-10-15},
  howpublished = {\url{https://sociolens-web.pages.dev/claims/ld09-sl-c14/v1.0/}},
  note = {Claim LD09-SL-C14, 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 30317c6bd9729368d9654d920bffac7cc18d23c9e1dbfac4a953b0a5a4eecc8b.

Repository-authored inputs (not Drive exports)

SocioLens claim — LD09-SL-C14 v1.0 (v1.0) — written in the SocioLens repository by Project Lead (Claude, AI) on 2026-10-15; 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 15 October 2026 to build the LD-09 debate; a new Claim, first version, written from the project's LD-09 source notes, checked against full texts or official abstracts. Block “ENTRY 14 — LD09-SL-C14” SHA-256 1c431a4f32f569fa7048f475f8aabb2f29e93590ff9e940702d9f00ba94ce2e4; fixture fixtures/authored/claims/LD09-SL-C14--v1.0.

Builder decisions (not Drive data)

VERSION = v1.0 — basis: Claim version taken from the repository-authored claim fixture version (SocioLens claim — LD09-SL-C14 v1.0); the first version of a new Claim of the LD-09 debate
CURRENT_POINTER = true — basis: repository-authored claim "SocioLens claim — LD09-SL-C14 v1.0" (Project Lead (Claude, AI), 2026-10-15); 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 15 October 2026 to build the LD-09 debate; a new Claim, first version, written from the project's LD-09 source notes, checked against full texts or official abstracts
FIELD_6_SOURCE_REFERENCE = SRC-SL-PADMAKUMAR-HE-ICLR-2024--v1.0 — basis: field 6 of ENTRY 14 — LD09-SL-C14 cites "Padmakumar & He, “Does Writing with Language Models Reduce Content Diversity?,” ICLR 2024, arXiv:2309.05196"; the only field-6 segment of this ClaimVersion's repository-authored ledger block.
SOURCE_PROVENANCE_PIN = SRC-SL-PADMAKUMAR-HE-ICLR-2024--v1.0 — basis: explicit version-pinned public provenance of this ClaimVersion (Amendment v1.2 §6): the pinned field-6 Source record "Padmakumar & He, “Does Writing with Language Models Reduce Content Diversity?,” ICLR 2024, arXiv:2309.05196".