CASRAI Dictionary

Tag: contributorship

  • Mentorship as a CRediT role: pro and con

    The CRediT Supervision role is broad. The role definition reads: Oversight and leadership responsibility for the research activity planning and execution, including mentorship external to the core team. The role bundles mentorship into Supervision, which leaves the question: should mentorship be a CRediT role of its own? This post lays out the arguments on both sides and proposes a mid-path.

    The case for

    Three arguments for a dedicated Mentorship role.

    First, visibility. Mentorship is a substantial intellectual and time-consuming activity that current CRediT-style contributorship statements largely render invisible. A senior researcher who mentored an early-career colleague through the discovery, the writing, and the navigation of peer review has contributed significantly to the paper; the current taxonomy captures this only through the catch-all Supervision role, which is also used for project oversight that is quite different in character.

    Second, career-stage equity. Mentorship contribution is most often delivered by mid-career and senior researchers to early-career ones, and is most often invisibilised in the way it currently is. Making it a CRediT role would help correct the under-recognition of mid-career mentorship work in promotion and tenure decisions. The mentorship and career stages domain at CASRAI tracks the assessment-side implications.

    Third, distinction from supervision. Project supervision (the senior researcher with PI responsibility) and mentorship (the senior or peer researcher who guided a junior contributor’s development through the work) are different activities. Bundling them into one role loses the distinction. A paper where the PI did the supervision and a separate mid-career colleague did the mentorship has a contributorship structure that current CRediT cannot express cleanly.

    The case against

    Three arguments against.

    First, taxonomic stability. CRediT has held to 14 roles deliberately. Each addition raises cognitive load and risks the taxonomy becoming unusable through over-specification. Liz Allen and the original CRediT designers have consistently argued that the taxonomy gains value from being small enough to use; adding a Mentorship role pushes against this.

    Second, boundary problems. What distinguishes mentorship from supervision, from teaching, from co-authorship, from collaboration? The lines are real but fuzzy. A senior colleague who reviewed the draft and suggested major revisions is doing Writing – review & editing; the same colleague who guided the junior author through how to think about the discovery is doing mentorship; in practice the activities overlap. A role that requires reviewers to distinguish them may produce noise more than signal.

    Third, recognition versus contribution. CRediT is a contributorship taxonomy, describing what people did on the paper. Mentorship is broader than per-paper contribution; it is a sustained relationship that spans many papers and many years. Capturing per-paper mentorship in CRediT may be the wrong instrument; a separate mentorship-recognition mechanism (in narrative CVs, in promotion dossiers, in institutional mentorship programmes) may fit better.

    A proposed mid-path

    We propose a mid-path that addresses the visibility and equity concerns without expanding the CRediT role count.

    First, clarify the Supervision definition. The current definition bundles mentorship with project leadership. The bundling could be unbundled within the existing role through definitional refinement: the role description could be revised to explicitly recognise mentorship as a sub-activity within Supervision, with guidance on when each is being discharged. This is a low-cost intervention that does not require a new role.

    Second, add a structured qualifier for Supervision. The existing degree-of-contribution qualifier already provides lead/equal/supporting. A sub-qualifier indicating whether the Supervision was project-oriented, mentorship-oriented, or both, would add the granularity without adding a role. This is a small schema change with substantial value.

    Third, build the recognition layer outside CRediT. The narrative-CV format, mentorship-specific recognition programmes, and institutional career-development frameworks should carry mentorship recognition at a sustained-relationship granularity that CRediT cannot. The mentorship recognition that early-career researchers most value is not the per-paper notation; it is the cumulative recognition of mentorship across a career. The CASRAI institutional mentorship guide walks through the recognition options.

    What CRediT v2026.3 should do

    Our recommendation for the v2026.3 revision discussion: do not add a Mentorship role; do refine the Supervision definition to recognise mentorship explicitly; do add a sub-qualifier capturing the project/mentorship/both distinction; do coordinate with the narrative-CV and institutional-recognition communities to ensure that the cumulative mentorship recognition picture is captured outside CRediT.

    This is the position we lean toward, with the explicit acknowledgment that reasonable people disagree. The discussion at the December 2025 CRediT stewardship meeting was substantive; the community consultation through 2026 will be the place to settle it. The CASRAI CRediT governance page tracks the consultation process and welcomes input from the broader community.

    A broader observation

    The mentorship question is one instance of a broader pattern. CRediT, as a per-paper contributorship taxonomy, captures certain things well and certain things less well. The work that spans papers (sustained mentorship, leadership of a community, contribution to standards, infrastructure stewardship) does not fit naturally into a per-paper taxonomy. The right response is not to expand CRediT to cover everything but to build complementary recognition mechanisms for what CRediT does not capture.

    This is the argument running through the responsible-assessment community, the narrative-CV adoption push, and the CoARA reform agenda. CRediT is part of the picture, not the whole picture. A senior researcher’s contribution profile is captured by CRediT statements on their papers, by their narrative CV, by their teaching record, by their mentorship record, by their service to the community. The integrated picture is the goal; CRediT is one component.

    Practical recommendations

    Three for institutions. First, capture mentorship in your institutional records and recognition systems; do not wait for it to be a CRediT role. Second, train promotion-and-tenure committees to read mentorship contribution explicitly when reviewing dossiers. Third, support narrative-CV formats that surface mentorship.

    Three for researchers. First, claim your mentorship contribution in narrative CVs and professional records; do not depend on per-paper CRediT to capture it. Second, in CRediT statements, use Supervision appropriately and consider noting the mentorship dimension in the prose contribution statement that accompanies the structured CRediT. Third, contribute to the CRediT consultation if you have a view on the question.

    Three for the CRediT stewardship community. First, run the v2026.3 consultation transparently and document the outcomes. Second, coordinate with the responsible-assessment community on the broader recognition picture. Third, treat the question of taxonomic expansion as a serious one with substantive trade-offs, not as a routine update.

    Related dictionary entries

  • CRediT for AI-generated content: where the line is

    The ICMJE 2023 position is settled: artificial-intelligence systems cannot be authors. The follow-on question that journals and authors continue to negotiate is how to represent, in a contributorship statement, the human work that goes into producing AI-assisted content. When a co-author prompts an LLM to draft a section, verifies the output, edits it, and stands behind it, which CRediT role describes their contribution? This post proposes a working line.

    The shape of the question

    Three scenarios make the question concrete.

    Scenario one: an author uses an LLM to polish prose in a draft they wrote. The intellectual content is theirs; the language is partly the model’s. The CRediT role is straightforwardly Writing – original draft for the author.

    Scenario two: an author uses an LLM to draft a first version of a section, which they then heavily revise. The first draft is the model’s; the final draft is the author’s, but the model substantively shaped what the final draft says. The CRediT role is still Writing – original draft for the author, but the contribution is meaningfully different from scenario one.

    Scenario three: an author uses an LLM to propose a study design, which they then refine. The intellectual content of the methodology was partly the model’s. The CRediT role is Methodology for the author, but again the contribution is meaningfully different from the unaided version.

    In all three, the human author is the role-holder; the model is not a co-author. What is different across the scenarios is the magnitude and the character of the human contribution. CRediT, as currently constituted, does not distinguish these.

    The working line

    Our proposed line is the verification-and-responsibility threshold. A human contributor who has substantively verified the AI-generated content, taken responsibility for it, and is prepared to defend it in correspondence or post-publication discussion is properly credited with the relevant CRediT role. The role describes what they contributed to the paper, which includes verification work even if the first-draft work was the model’s.

    The line shifts where the human contribution is insubstantial — a contributor who pasted a prompt, accepted the output without verification, and added their name to the paper has not discharged the role and should not be credited. This is the same line that has always applied to non-AI cases (a co-author who did not contribute should not be credited; gift authorship is a well-recognised failure mode).

    The line is therefore not about AI use per se; it is about whether the human contribution clears the substantive-contribution threshold. AI use does not displace the threshold; it changes what discharging the role looks like in practice.

    Disclosure runs parallel

    The disclosure of AI use is a separate question, addressed via publisher-mandated AI disclosure declarations. The disclosure says what tools were used and for what; the CRediT statement says who contributed what to the paper. The two run parallel and are both required by most major publishers in 2026. The CASRAI AI disclosure for authors guide walks through the publisher-by-publisher requirements.

    Implications for specific roles

    Writing – original draft

    The most common case. A human author whose draft was AI-assisted is properly credited with Writing – original draft if they verified the content, took responsibility for it, and produced the version that is the paper. The disclosure declaration says the AI was used; the CRediT statement names the human as the writer-of-record.

    Methodology and Formal analysis

    More delicate. If an AI-assisted statistical-discovery tool proposed a method or an analytic approach, the human contributor’s role is partly verification (was the proposal sound?) and partly extension (refining the proposal into the actual method). The CRediT role is still Methodology and/or Formal analysis for the human, but the verification dimension is foregrounded. If the human did not verify — accepted the AI proposal without independent assessment — the contribution is weaker and may not clear the role threshold.

    Investigation

    A subtle case. AI-assisted data extraction (e.g., from imaging, from medical records, from text corpora) involves a human contribution that runs from setup through verification to interpretation. Investigation includes the data-gathering activity; an AI-assisted version still has a human Investigation lead, who is responsible for the setup, the verification of extracted data, and the handling of errors.

    Validation

    Perhaps the most directly affected. Where AI tools are used for cross-checking, sensitivity analyses, or reproduction of results, the human Validation contributor is responsible for setting up the validation, interpreting its results, and acting on discrepancies. The AI does the mechanics; the human does the judgement.

    Visualization

    AI-assisted figure generation is increasingly common. The human Visualization contributor is responsible for the figure-design decisions, for verifying that the AI-generated figure accurately represents the data, and for the final version that appears in the paper. Where the AI generated an image that the human did not substantively verify, the threshold may not be cleared.

    The role-as-recognition trap

    A failure mode to flag explicitly. The temptation, when AI did most of the actual production work, is to inflate the human contributor’s role assignment to compensate. “The AI wrote the draft, but I prompted it, so I should still be Lead on Writing – original draft.” This is a misreading. The CRediT role is a description of contribution; if the human contribution was “prompted and accepted”, that is a smaller contribution than “drafted, verified, revised, took responsibility.” Calling both “Lead” obscures the difference.

    The remedy is the degree-of-contribution qualifier. A human contributor whose AI-assisted contribution was substantial may be Lead; one whose contribution was lighter may be Supporting. The qualifier discipline forces an honest assessment of magnitude.

    Where this leaves the AI-assistance-role question

    We have argued elsewhere that a 15th CRediT role explicitly for AI assistance is worth considering. The argument from this post is partly orthogonal: the existing 14 roles can accommodate AI-assisted work if the verification-and-responsibility threshold is honoured and the qualifier is used honestly. The case for a 15th role rests on whether the structured disclosure-of-AI-use is better placed inside the contributorship statement or outside it. Reasonable people disagree; we lean toward keeping AI disclosure parallel to CRediT rather than inside it, with attention to the verification-and-responsibility line.

    Practical recommendations

    Three for authors. First, treat AI assistance as a tool, not a substitute. Verify, edit, and take responsibility for what appears in the paper. Second, assign CRediT roles based on what you contributed including verification, not based on what the AI produced. Third, disclose AI use in the publisher-mandated declaration; the disclosure runs parallel to CRediT, not inside it.

    Three for editors. First, treat the verification-and-responsibility threshold as the operating standard for AI-assisted contributorship. Second, require both the CRediT statement and the AI-use disclosure at submission. Third, where a contributorship statement looks like it may reflect AI-assistance role inflation, ask the standard editorial question: what did this contributor actually do?

    Three for the broader system. First, harmonise AI-disclosure formats across publishers (work the NISO and COPE community has begun). Second, maintain the contributorship-versus-disclosure separation; do not collapse them. Third, evaluate the case for a 15th CRediT role on its merits, including the costs of taxonomic expansion.

    Related dictionary entries

  • How to write a CRediT statement for medical research in 2026

    Medical-research contributorship sits at an awkward intersection. The International Committee of Medical Journal Editors (ICMJE) still defines who may sign as an author of a clinical paper through its four-part test: substantial contribution to conception/design or acquisition/analysis/interpretation; drafting or critical revision; final approval; and accountability. CRediT, the Contributor Roles Taxonomy that CASRAI helped steward into NISO Z39.104-2022, sits underneath and describes what each named contributor actually did. In 2026, after another wave of journal adoption and the long-anticipated alignment with ORCID’s contributor affiliation model, a CRediT statement is no longer a discretionary nicety. It is the contributorship record of the paper.

    This post walks through how to write a CRediT statement that satisfies a medical journal’s submission system in 2026, with attention to the editorial conventions of NEJM, The Lancet, JAMA, and The BMJ. It assumes you have already worked out who meets the ICMJE authorship threshold; see our medical-research authors guide for that step.

    Authorship versus contributorship: not the same question

    The first error we see in submissions is conflating ICMJE authorship with CRediT contributorship. ICMJE answers a binary: does this person qualify to be listed as an author and to be accountable for the work? CRediT answers a granular: of the people who are listed, who did what? A statistician who ran the analysis but did not draft or revise may not meet ICMJE criteria and is acknowledged separately; if they do meet ICMJE criteria, then their CRediT role assignment would include Formal analysis, possibly Methodology, possibly Software, and they would be named on the byline. Liz Allen and the team that originated CRediT at Wellcome Trust were explicit on this distinction; the taxonomy was designed to complement, not replace, journal authorship rules.

    For medical research the second confounder is the guarantor. The BMJ has long required a named guarantor in addition to authors, and other ICMJE-following journals encourage the convention for clinical trials. The guarantor sits outside CRediT; it is closest in spirit to the Supervision role plus an accountability commitment, but it is not encoded in the taxonomy. In your CRediT statement, name the guarantor in a separate sentence; do not invent a Guarantor role.

    The 14 roles in medical-research context

    CRediT’s 14 roles were drafted for general research and need a brief translation when applied to clinical work. The full role definitions are normative; what follows is interpretive guidance, not a redefinition.

    • Conceptualization. The research question. For a registered clinical trial this is often a Principal Investigator role; for a secondary analysis it may be a junior contributor with a novel hypothesis.
    • Methodology. Study design, choice of endpoints, statistical-analysis-plan structure. A trial statistician contributing to the SAP earns this role even if a different person ran the final analysis.
    • Software. Programming for data capture (REDCap configuration counts), randomisation code, custom statistical packages, any analytic script that materially shaped results.
    • Validation. Reproduction of analyses, sensitivity analyses, cross-checks against an independent dataset. Often a co-author who replicates the lead analyst’s work.
    • Formal analysis. The statistical analysis itself.
    • Investigation. Recruitment, screening, consenting, clinical assessments, sample collection. Often the largest list of contributors in multi-site trials.
    • Resources. Provision of patient samples, biobanks, animal models, instrument time. Distinct from Funding acquisition.
    • Data curation. Data cleaning, harmonisation, query resolution, lock-down.
    • Writing – original draft. First-draft authorship of the manuscript.
    • Writing – review & editing. Substantive editorial revision, not copy-editing.
    • Visualization. Figures, including Kaplan-Meier curves, forest plots, CONSORT flow diagrams.
    • Supervision. Mentorship and oversight, often the senior author. A PI typically combines Supervision with Conceptualization and Funding acquisition.
    • Project administration. Coordination across sites, ethics submissions, sponsor liaison.
    • Funding acquisition. Grant-writing for the funded work.

    The lead/equal/supporting qualifier

    Adopted formally into NISO Z39.104 and now widely supported, the degree-of-contribution qualifier resolves a recurring source of disputes. For each role, exactly one contributor may be marked Lead, or several may be marked Equal; everyone else for that role is Supporting. In a multi-site oncology trial it is realistic to have a Lead Investigator (the coordinating PI), several Equal Investigators (site PIs), and a longer list of Supporting Investigators (sub-investigators, research nurses who meet ICMJE thresholds). The qualifier exists precisely so that the byline order does not have to encode contribution magnitude.

    Writing the statement

    A 2026-compliant CRediT statement is rendered as prose in the manuscript and as structured data in the submission system. Most major medical journals now extract the structured form from their submission portal directly; the prose paragraph is for the published version. Here is a worked example for a four-author RCT report:

    CRediT author statement. Sarah Chen: Conceptualization (lead), Methodology (lead), Funding acquisition (lead), Supervision (lead), Writing – review & editing (equal). Marcus Okonkwo: Investigation (lead), Project administration (lead), Data curation (lead), Writing – original draft (lead). Priya Raman: Formal analysis (lead), Software (lead), Validation (lead), Visualization (lead), Writing – review & editing (equal). David Holcombe: Methodology (supporting), Investigation (supporting), Writing – review & editing (supporting), Supervision (supporting). Guarantor: Sarah Chen.

    Note the explicit guarantor statement, separate from CRediT. Note also that not every role appears; Resources was inapplicable here and should be omitted rather than padded.

    JATS XML output

    For machine-actionable contributorship, journals serialise CRediT into JATS XML using the <role> element with the vocab="credit" attribute and the canonical role URI. The 2022 NISO version pinned the URIs at https://credit.niso.org/contributor-roles/<role-slug>/ with the qualifier expressed via specific-use="lead|equal|supporting". As an author you do not write the JATS by hand; you fill in the submission portal and the publisher’s tooling renders the XML. Where things go wrong is the round-trip: if the published HTML drops the qualifier, the JATS may also drop it and downstream Crossref deposits will be incomplete. If you care about the persistent record, check the published JATS via the publisher’s content syndication endpoint after acceptance.

    Journal-specific notes

    NEJM

    The New England Journal of Medicine adopted CRediT in late 2023 and integrated it into its Editorial Manager workflow in 2024. NEJM’s idiosyncrasy is that it still asks separately for the prose contribution statement, then asks each author to confirm their CRediT roles, and finally requires a writing-assistance declaration that is not CRediT (it covers professional medical writers funded by sponsors). Do not list a paid medical writer who does not meet ICMJE criteria under CRediT Writing – original draft; declare them in the acknowledgements with the funding source per Good Publication Practice (GPP 2022).

    The Lancet

    The Lancet was an early CRediT adopter and was unusual in coupling the taxonomy to a long-standing requirement for each author to write a one-sentence prose contribution statement in their own words. Both are retained in 2026. The prose statement is what readers see in the printed acknowledgements; the structured CRediT data lives in the JATS and in Crossref. For a Lancet submission, write the structured assignment first and then have each author translate their own roles into a single readable sentence.

    JAMA

    JAMA and the JAMA Network journals adopted CRediT in 2022 and tied it tightly to ORCID; an author without a verified ORCID iD cannot complete the contributorship form. JAMA also asks for explicit role assignments for Statistical analysis, Obtained funding, and Administrative, technical, or material support; these are journal-specific role labels that overlap with CRediT but are tracked separately for editorial QA. If you have a Formal analysis role under CRediT you must also tick Statistical analysis on the JAMA form, otherwise the submission will not validate.

    The BMJ

    The BMJ adopted CRediT in 2023 and retained its long-standing guarantor requirement on top. BMJ’s submission system asks for the CRediT roles in structured form and then asks the corresponding author to identify the guarantor by name. The published article carries both: the CRediT statement as prose, and the guarantor sentence beneath it. BMJ also continues to require declarations of relationships and activities (the BMJ-specific competing interests format) which sit alongside but separately from CRediT.

    Common failure modes

    Three patterns recur in submissions to medical journals. First, role inflation: assigning Conceptualization to every author by reflex. CRediT is a record, not a recognition device; if a co-author did not contribute to conceptualisation, do not assign that role. Second, byline order substituting for qualifiers: a paper with five equal first-authors should mark all five as Equal on the roles they share, not just rely on a footnote saying “these authors contributed equally.” Third, missing the writing roles: every paper has someone who wrote the first draft. If your CRediT statement omits Writing – original draft, the editor will ask.

    Adoption status and trajectory

    As of early 2026 the CRediT adoption ledger records 70+ publishers with active CRediT support and structured submission workflows in most major medical and biomedical journals. The ICMJE has not made CRediT mandatory across its full membership, but its 2024 update to the Recommendations explicitly endorses CRediT as an acceptable mechanism for describing contributions, and several ICMJE journals require it. Outside ICMJE, the trajectory is the same: PLOS, Cell Press, Springer Nature, Wiley, Taylor & Francis, Elsevier, OUP, CUP, and a long tail of society publishers now require structured CRediT at submission.

    What to do next

    If you are preparing a submission, work through these in order: (1) settle the authorship list against ICMJE criteria; (2) draft the CRediT role assignment in a shared document with qualifiers; (3) have each author confirm their roles in writing before submission; (4) enter the structured data in the submission portal and copy the prose statement into the manuscript; (5) declare the guarantor and any medical writers separately. The CASRAI CRediT authors guide contains a downloadable role-assignment worksheet that has saved more co-author disputes than any other artefact we publish.

    Related dictionary entries

    References

    ICMJE, Recommendations for the Conduct, Reporting, Editing, and Publication of Scholarly Work in Medical Journals (2024 update). NISO Z39.104-2022, CRediT, Contributor Roles Taxonomy. Allen et al., Nature (2014), Publishing: Credit where credit is due. Brand et al., Learned Publishing (2015), Beyond authorship: attribution, contribution, collaboration, and credit. Holcombe, Publications (2019), Contributorship, not authorship.

  • Three CRediT misuses we see in submitted papers

    CASRAI’s editorial network includes journal editors who handle CRediT statements daily, and we periodically aggregate the patterns of misuse they see. Three failures recur across disciplines, journal sizes, and submission systems. None are scandalous; all are correctable with attention. This post catalogues them with concrete examples and the editorial responses that work.

    Failure one: role inflation

    Role inflation is the most common CRediT failure by a wide margin. It is the practice of assigning every author every role, or near-every role, regardless of what they actually did. A typical inflated statement reads like a litany: Author A: Conceptualization, Methodology, Investigation, Formal analysis, Data curation, Writing – original draft, Writing – review & editing, Visualization, Supervision, Funding acquisition, Project administration. Author B: Conceptualization, Methodology, Investigation, Data curation, Writing – review & editing. Author C: Conceptualization, Methodology, Writing – review & editing. Every author is conceptualisation-positive; every author methodology-positive; every author writing-positive.

    The pattern is recognisable and almost always wrong. Five authors did not all conceive the study. Five authors did not all design the method. Five authors did not all write the original draft. Role inflation reflects a misunderstanding of what CRediT is for: it treats the role assignment as a credit allocation (the more roles you have, the more credit you get), when CRediT is a description of contribution. As Liz Allen and the original CRediT designers were explicit, the taxonomy is meant to record what each contributor actually did, not to maximise their visible role count.

    The editorial fix

    Editors increasingly push back at submission. The Lancet‘s convention of requiring each author to write a prose contribution statement in their own words is unusually effective; it forces a moment of reflection on what the author actually did. Several other journals have adopted variations. The CASRAI CRediT authors guide includes a role-assignment worksheet that asks each author to write a one-sentence justification per role before the statement is finalised; the discipline of writing the justification surfaces most cases of role inflation before submission.

    Where inflation has already made it into a submission, the editorial response is to ask the corresponding author to revise. The framing that works is methodological: “We use CRediT to describe what each contributor actually did. Please review the role assignments and confirm that each role corresponds to a substantive contribution by that author.” This is rarely contentious; in our experience the corresponding author tightens the statement on review.

    Failure two: byline order substituting for qualifiers

    The degree-of-contribution qualifier was added to NISO Z39.104 specifically to resolve byline-order disputes. A paper with three co-first-authors should mark them all as Equal on the roles they share; a paper with a clear lead on one role and supporting contributors on others should use Lead and Supporting accordingly. The qualifier is structurally what byline order has long tried to encode implicitly.

    The misuse we see is statements that ignore the qualifier and rely on byline order or footnotes to communicate contribution magnitude. A typical example: a paper with five authors and a footnote saying “authors 1 and 2 contributed equally” but a CRediT statement that assigns roles without qualifiers, leaving the reader to infer what “equally” means across the roles. Is author 1’s Investigation equal to author 2’s Investigation? Is author 1’s Formal analysis equal to author 2’s Formal analysis? The footnote does not say; the unqualified CRediT statement does not say.

    The editorial fix

    Adopt the qualifier explicitly. If two authors contributed equally to a role, mark both Equal on that role. If one author was the lead and others supported, mark Lead and Supporting. Footnotes about equal contribution become redundant; the structured statement carries the information.

    For journals, the editorial implementation is to require the qualifier in the submission system. The CRediT JATS specification supports the qualifier via the specific-use attribute; submission systems should expose this and require it. A few publishers have already moved here; we expect most to follow through 2026.

    Failure three: missing writing roles

    Every paper has someone who wrote the first draft. If a CRediT statement omits Writing – original draft, the editor will ask. This is the third recurring failure: statements that distribute Methodology, Investigation, Formal analysis, and Supervision but leave Writing – original draft unassigned.

    The pattern usually reflects a real ambiguity. In a paper with three co-equal authors who jointly drafted, who gets Writing – original draft? The answer is all three, marked Equal. In a paper where a postdoc drafted under supervision and a senior author heavily revised, who gets which writing role? Almost always: postdoc gets Writing – original draft (lead); senior author gets Writing – review & editing (lead). In a paper where a paid medical writer drafted, the medical writer is typically not an author per ICMJE — they are acknowledged separately — and the authors who substantively shaped the draft get Writing – original draft as appropriate.

    The editorial fix

    Editors should treat “who wrote the first draft” as a required question at submission. The BMJ asks this explicitly. The CASRAI worksheet asks it. If the statement does not name a Writing – original draft contributor, the editor’s standard response is a one-line query: “Please indicate which author or authors discharged the Writing – original draft role; the role is currently absent from the CRediT statement.” In our editor network this query gets a fast, accurate response and the role is added before review proceeds.

    Three lesser failures worth a paragraph each

    Beyond the big three, three lesser failures are worth noting. First, conflating Methodology and Formal analysis: the role definitions distinguish these (Methodology is the study design; Formal analysis is the statistical or analytical work on the resulting data) and assigning both to the same person without distinction loses information. Second, assigning Software to anyone who touched a computer: Software is meaningful programming work, not opening Excel; if the contributor wrote no code, did not script the analysis, did not configure REDCap, they probably did not discharge the Software role. Third, missing Funding acquisition: someone wrote the grant. If the CRediT statement does not name a Funding acquisition contributor and the paper is grant-funded, the role is missing.

    What CASRAI recommends

    Four practical recommendations. First, use the role-assignment worksheet at the drafting stage, not at submission; it catches most misuse early. Second, require the degree-of-contribution qualifier in your journal submission system. Third, treat missing Writing – original draft as a default editorial query. Fourth, when in doubt about role inflation, ask each author to write a one-sentence justification per role; the discipline reveals the over-assignment naturally.

    For the broader system, the most useful intervention is journal submission system support. Adoption at the policy level is now widespread, but the per-submission UX varies enormously. A submission system that prompts for qualifiers, validates that every role has a contributor, and asks per-author confirmation of role assignment catches most failures before they reach editorial review. We expect this UX to converge through 2026 as publishers update their Editorial Manager and ScholarOne configurations.

    Related dictionary entries

  • Why the next CRediT version should include ‘AI assistance’ as a role

    The 14 roles of CRediT were designed in 2013-2014 with a model of contribution that did not include large language models or generative AI systems. A decade on, the taxonomy is robust and widely adopted, but the AI question is hard to ignore. This post makes the case — tentatively, and with attention to the counter-arguments — that the next CRediT revision should add a 15th role explicitly covering AI assistance. We are publishing it here to invite community pushback before any formal proposal goes to the CRediT stewardship group.

    Why this question is not solved by disclosure alone

    The current consensus around generative AI in scholarly authorship rests on two pillars: AI cannot be a co-author (the ICMJE 2023 position), and AI use must be disclosed in a structured declaration. CASRAI agrees with both. They do not, however, resolve the question of how AI assistance shows up in CRediT.

    A worked example. Suppose a paper has four authors. Author A wrote the first draft with substantial assistance from a large language model, which she prompted, edited, fact-checked, and revised. Author B ran the formal analysis using an AI-assisted statistical-discovery tool that proposed model specifications. Author C generated several of the figures using a GenAI visualisation tool. Author D supervised. Each used AI; each used it differently; each took human responsibility for the output. How does the CRediT statement represent this?

    Under current CRediT, AI use is invisible. Author A gets Writing – original draft (lead). Author B gets Formal analysis (lead). Author C gets Visualization (lead). Author D gets Supervision. The AI assistance shows up only in the publisher-mandated AI disclosure, which is a free-text field in the methods or acknowledgements. The structured contributorship record has no place for the granular fact that AI was a tool in each of those role-discharges.

    The proposed 15th role

    The draft scope we are testing is this:

    AI assistance. The use of artificial-intelligence systems, including generative AI, machine-learning models, and automated analytical tools, in the production of the work. Includes prompt engineering, model selection, validation of AI output, and human verification of AI-generated content. Does not include use of AI as a routine tool (e.g., grammar checkers, citation-formatting tools) below a disclosure threshold defined by the publisher.

    The role would carry the standard degree-of-contribution qualifier. A human author whose primary contribution was prompting and verifying an AI system would be marked Lead for AI assistance; a co-author who occasionally checked AI outputs would be Supporting. The role would not be a substitute for the existing roles — the human who used AI for the first draft still gets Writing – original draft — but it would add the structured fact that AI was involved.

    The arguments for

    First, structured disclosure is more useful than prose disclosure. A free-text AI declaration cannot be queried, cross-referenced, or aggregated. A CRediT-style structured role can. Integrity offices investigating a fabrication can query for papers with AI assistance roles; funders tracking AI use in grant outputs can roll up the data; bibliometric studies can analyse patterns. None of this is possible with the current free-text disclosure.

    Second, granularity matters for accountability. Knowing that a paper used AI is less useful than knowing which contributor used AI for which task. The CRediT role assignment makes the accountability specific. If a fabricated reference appears in the introduction, the question of who is responsible for verifying it has a structured answer.

    Third, the boundary is becoming a fiction. Modern statistical workflows include AI components (autoML, AI-assisted exploratory analysis); modern writing workflows include AI components (Copilot for prose, Claude for editing); modern visualisation workflows include AI components. The pretence that these are separable from the role they support is increasingly hard to maintain. If AI is being used to discharge a role, the role assignment should say so.

    The arguments against

    Three serious counter-arguments deserve engagement.

    First, the scope-creep concern. CRediT has held to 14 roles deliberately. Each addition raises the cognitive load on authors filling out the statement, increases the integration burden on publishers, and risks the taxonomy becoming unusable through over-specification. The argument from Liz Allen and the original CRediT designers has been that the taxonomy gains its value from being small enough to use.

    Second, the boundary problem. What counts as AI assistance? A grammar checker is plausibly AI; a citation formatter increasingly is; a search engine ranking results by relevance certainly is. If every modern research tool counts as AI, the role becomes meaningless. A workable scope requires a non-trivial threshold (the draft language above gestures at “below a disclosure threshold defined by the publisher”), and that threshold is hard to define without ending up with either everything or nothing.

    Third, the disclosure-versus-contribution distinction. CRediT is a contributorship taxonomy. AI is not a contributor — that is the settled position. Adding an AI role to CRediT risks blurring this. The alternative is to keep AI in a separate disclosure form, structurally similar to a competing-interests declaration or a funding statement, rather than in the contributorship statement.

    A possible middle path

    The middle path is to keep CRediT at 14 roles and to define a parallel AI assistance declaration with comparable structure: a controlled vocabulary of AI-use types, a per-contributor breakdown linked to ORCID iDs, a model-and-version field, and a verification statement. This would sit alongside CRediT in publisher submission systems and JATS XML, rather than inside it.

    This is closer to where the current publisher disclosure forms are heading, and it preserves the conceptual clarity that CRediT roles describe what humans did, while a separate declaration describes what AI tools were used. We are increasingly inclined to recommend this path, with the caveat that the disclosure must be structured to the same standard as CRediT — not free-text, with controlled vocabularies, deposited to Crossref, and surfaced on ORCID.

    What the CRediT stewardship group should do next

    Three concrete steps. First, run a structured community consultation through 2026 on whether to add AI assistance as a 15th CRediT role, with the alternative being a parallel structured declaration. The CRediT governance page outlines the consultation process. Second, in parallel, draft the data model for a parallel AI assistance declaration so that the comparison is concrete and not abstract. Third, coordinate with NISO on whether either option requires a revision to Z39.104.

    The decision is not urgent in the sense that the integrity system is failing today; the existing disclosure forms work, badly. It is urgent in the sense that every year of delay produces another year of unstructured AI-use data that cannot be aggregated or analysed, which makes the eventual transition harder.

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