CRediT, ICMJE, and the authorship landscape

Last updated: 2026-05-17

Synthesis

Authorship in modern science is increasingly contested, increasingly formalised, and increasingly machine-readable. Two complementary artefacts dominate the landscape: ICMJE’s four authorship criteria (substantial contribution, drafting, approval, accountability), which define who can be an author; and the Contributor Roles Taxonomy (CRediT), which describes what each contributor actually did, mapping contributions onto 14 standardised roles. The empirical literature on ghost and gift authorship shows the older “author list” model has been quietly failing for decades: roughly one in five high-impact biomedical papers in 2008 reported either honorary or ghost authorship [3]. The combination of CRediT metadata plus explicit ICMJE compliance is the field’s response.

The 2023 ICMJE update making LLMs ineligible for authorship [5] is relevant for scriptorium beyond the obvious “don’t list ChatGPT as a co-author” — it implies that any AI-assisted scholarly tool must be disclosable, attributable, and ultimately reducible to a human’s accountability. Scriptorium’s design is consistent with this: skills are explicitly invoked, outputs are reviewed by humans, and the underlying manuscript remains a human-accountable artefact.

For the build itself: this is a schema-level addition, not a new skill. MANUSCRIPT_STATE.yaml should grow a contributors: field aligned to CRediT roles. Several v0.x skills can then consume it without a dedicated authorship skill being justified.

Evidence and frameworks

CRediT: the 14 roles

The Contributor Roles Taxonomy was developed through a workshop process beginning in 2012, formalised by Brand et al. in 2015 [1], and adopted by CASRAI and (later) NISO. As of the mid-2020s, more than 150 publishers reference CRediT in their submission workflows.

The 14 roles are:

1. Conceptualization
2. Data curation
3. Formal analysis
4. Funding acquisition
5. Investigation
6. Methodology
7. Project administration
8. Resources
9. Software
10. Supervision
11. Validation
12. Visualization
13. Writing — original draft
14. Writing — review & editing

Each contributor can hold multiple roles, and roles can be marked “lead”, “equal”, or “supporting”. The point is to disaggregate “author” into “what did this person actually contribute”, which is where the older author-list model breaks down for large collaborations.

The 2015 Brand et al. paper [1] frames CRediT as “moving beyond authorship” toward an “attribution” model — useful background for why the taxonomy looks the way it does.

ICMJE: the four criteria

The International Committee of Medical Journal Editors specifies four conditions, all of which must be met, for someone to be listed as an author:

1. Substantial contributions to the conception or design of the work, or the acquisition, analysis, or interpretation of data.
2. Drafting the work or reviewing it critically for important intellectual content.
3. Final approval of the version to be published.
4. Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Contributors who do not meet all four criteria should be listed in the acknowledgements with their specific contributions described. The ICMJE explicitly notes that funding, supervision, and data-acquisition alone do not justify authorship — a common source of dispute.

Ghost, gift, and honorary authorship

Wislar et al.’s 2011 BMJ cross-sectional survey [3] is the canonical empirical study. Across six leading general medical journals in 2008:

• Honorary authorship (named author who did not meet ICMJE criteria): 17.6%.
• Ghost authorship (substantive contributor not named as author): 7.9%.
• Either or both: 21.0%.

This was an improvement over the 1996 baseline (29.1%), but the absolute rate remains substantial. The literature distinguishes:

• Gift authorship — author added as a favour (mentor, senior colleague, collaborator on a different project).
• Honorary authorship — author added in deference to position or to confer credibility (department chair, funding-source representative).
• Ghost authorship — substantive contributor (often a professional medical writer, industry employee, or student) omitted from the byline.

The CRediT taxonomy is partly a response: explicit role assignment makes it harder to add an honorary author with no plausible contribution, and harder to omit a ghost author who did the heavy lifting.

Authorship order by field

Order conventions vary substantially across disciplines (see discipline-conventions):

• Biomedicine and life sciences: first author = lead contributor (often graduate student/postdoc); last author = senior responsible PI / corresponding author. Middle authors ordered approximately by contribution. Equal-contribution markers (†, *, “these authors contributed equally”) are common for first-author shared positions.
• Mathematics, theoretical physics, economics: alphabetical by surname. Deviation from alphabetical is sometimes meaningful and sometimes a journal style.
• Computer science / ML: contribution-based, no consistent field convention; lead author is typically first, advisor often last but not always.
• Particle physics (“hyperauthorship”): hundreds-to-thousands of authors listed alphabetically by collaboration convention; byline is unreadable as a contribution signal.

A scriptorium audit that assumes “last author = senior PI” silently mislabels mathematics and economics submissions.

AI and authorship policy

ICMJE’s 2023 update [5] is explicit: chatbots and LLMs cannot be listed as authors because they cannot satisfy the accountability criterion. Nature, Science, JAMA, and the Cell Press journals have issued aligned statements; the consensus is robust. Required disclosure varies:

• AI used for writing, editing, proofreading → describe in acknowledgements.
• AI used for data collection, analysis, or figure generation → describe in methods.
• Cover letter must mention AI use.
• Peer-reviewer confidentiality: uploading a manuscript to an LLM under review violates confidentiality unless the LLM is contractually non-retaining.

This last constraint is operationally relevant for reviewer-simulation: a user running the skill on their own unsubmitted manuscript is fine; a user running it on a manuscript they are peer-reviewing is not.

How this informs scriptorium

1. Add contributors: to MANUSCRIPT_STATE.yaml. Structure: a list of {name, orcid?, roles: [CRediT role string]} objects. This unblocks several downstream skills without requiring a new authorship-specific skill in v0.1.

2. Skills that consume contributors:

   • reviewer-simulation can flag authorship-policy issues (missing contribution statement, last author shown as non-contributor, AI listed as author).
   • A future submission-readiness audit can check ICMJE compliance pre-submission.
   • revision-summary can attribute changes to specific contributors when journals require it.

3. AI-disclosure language as a skill output. Scriptorium itself is an AI-assisted tool. Outputs of transformation skills should be invoke-traceable enough that users can write honest acknowledgements (“Scriptorium’s argumentative-flow skill was used to review the discussion section; all edits were reviewed by the authors”). This is a MANUSCRIPT_STATE /skill-log discipline, not a new skill.

4. Discipline-specific authorship-order norms. A scope warning in the schema documentation: contribution-order interpretation is biomedical-default; in math/economics, alphabetical order is not informative.

Implementation priority for scriptorium

Verdict: Yes (v0.1 schema augmentation) and No (no dedicated authorship skill).

Yes — schema: Add contributors: to MANUSCRIPT_STATE.yaml in v0.1 or v0.2. Minimal effort, high downstream leverage. Required data: a list of {name, orcid?, roles: [string]} items; roles drawn from the 14 CRediT categories; optional equal_contribution and corresponding booleans. Document the field in the schema, with a note that biomedical authorship-order conventions inform roles but other disciplines may use the field differently.

No — dedicated skill: A standalone authorship-audit skill is not justified in v0.1–v0.3. The cost of building it is disproportionate to how often a user will invoke it. Embed ICMJE-compliance checks in reviewer-simulation and (future) submission-readiness instead.

If Maybe later: if a non-trivial fraction of users start submitting to high-stakes biomedical venues where authorship disputes are a known failure mode, promote to a authorship-and-contribution-audit skill. Trigger: a user reports that an authorship issue was caught at submission that scriptorium could have flagged.

Open questions / weak evidence

• CRediT adoption is uneven: many adopting publishers require role metadata at submission but don’t publish it visibly, so its audit value depends on whether downstream readers can see it.
• The Wislar et al. data are 15+ years old. More recent surveys exist but are heterogeneous; the field-wide trend is unclear.
• AI authorship policy is evolving fast. The ICMJE position is robust, but specifics (do you need to disclose grammar checkers? citation managers? Paperpal?) are inconsistent across journals.
• ORCID integration with CRediT is improving but is not yet universal; some publishers require ORCIDs for all authors, others only the corresponding author.

References

[1] Brand, A., Allen, L., Altman, M., Hlava, M., & Scott, J. (2015). Beyond authorship: attribution, contribution, collaboration, and credit. Learned Publishing, 28(2), 151–155. DOI: 10.1087/20150211.

[2] International Committee of Medical Journal Editors. Defining the Role of Authors and Contributors. https://www.icmje.org/ recommendations/browse/roles-and-responsibilities/ defining-the-role-of-authors-and-contributors.html.

[3] Wislar, J. S., Flanagin, A., Fontanarosa, P. B., & DeAngelis, C. D. (2011). Honorary and ghost authorship in high impact biomedical journals: a cross sectional survey. BMJ, 343, d6128. DOI: 10.1136/bmj.d6128. PMID: 22028479.

[4] CRediT — Contributor Roles Taxonomy. https://credit.niso.org/. (Hosted by NISO since 2022.)

[5] International Committee of Medical Journal Editors. (2023). ICMJE Recommendations, updated May 2023. AI / chatbot authorship guidance. https://www.icmje.org/news-and-editorials/updated_recommendations_may2023.html and https://www.icmje.org/recommendations/browse/ artificial-intelligence/ai-use-by-authors.html.

[6] Allen, L., O’Connell, A., & Kiermer, V. (2019). How can we ensure visibility and diversity in research contributions? How the Contributor Role Taxonomy (CRediT) is helping the shift from authorship to contributorship. Learned Publishing, 32(1), 71–74. DOI: 10.1002/leap.1210.