CASRAI Dictionary

Tag: hidden labour

  • Recognising mentorship and training contributions in the research record

    Ask any senior researcher what they are proudest of, and a striking number will name the people they trained rather than the papers they wrote. Yet mentorship and training are almost entirely invisible in the formal research record. There is no DOI for supervising a doctoral researcher to completion, no citation count for the postdoc you helped launch, no structured field anywhere that records the years of pastoral and intellectual labour that hold a research group together. This is the archetypal hidden labour of research, and a cluster of recent developments is beginning to make it countable. This article surveys them, drawing on the mentorship and career-stages domain.

    Why the gap exists

    The formal record evolved to capture outputs — articles, books, patents, datasets — because outputs are discrete, attributable, and citable. Mentorship is none of those things. It is continuous, diffuse, and its effects show up years later in someone else’s career. The traditional CV gestures at it (“supervised 12 PhD students”) but in a form that is unverifiable, uncomparable, and easy to inflate. The result is a systematic under-recognition of exactly the work that sustains research culture, and a corresponding incentive to neglect it in favour of countable outputs.

    Narrative CVs: making space for the contribution

    The most consequential development is the shift toward narrative CVs. The UK Research and Innovation funder, UKRI, made its Résumé for Research and Innovation (R4RI) format standard across all its funding from January 2024; the Royal Society’s Résumé for Researchers preceded it, and Wellcome and others run comparable formats. These replace the enumerated publication list with a structured narrative organised around contribution types — and, crucially, they explicitly ask researchers to describe their contributions to people and to the research community, not only to knowledge.

    The R4RI structure asks for contributions across several modules, one of which is explicitly about the development of individuals — mentoring, supervision, team-building, and support for others’ careers. For the first time in a mainstream funding format, “I mentored three early-career researchers into independent positions” is not a throwaway line at the bottom of a CV but a first-class, evaluated contribution. The narrative form is what makes this possible: mentorship resists enumeration, but it can be described, and a good narrative description is assessable by a panel in a way that a raw number never was.

    Career-stage vocabulary: the precondition for fair comparison

    Recognising mentorship fairly requires knowing who is being mentored and where they are in their career — which requires a shared career-stage vocabulary. The terms look mundane but their absence causes real unfairness. A doctoral researcher, a postdoctoral researcher, an early-career researcher, a mid-career researcher, an established researcher — these are not interchangeable, and the expectations attached to each differ. Funder definitions of “early-career” vary widely, which means a researcher can be eligible for an ECR scheme in one country and not in another for no principled reason.

    Just as important are the terms for career breaks — parental, caring, illness, military service — and for part-time and fractional working. These exist in the vocabulary for a specific reason: responsible-assessment regimes expect evaluators to make career-stage adjustments, judging a researcher’s track record relative to the time and circumstances they actually had. A researcher who took two years of parental leave and works at 0.6 FTE should not be assessed as though they had a continuous full-time career. None of that is possible without a controlled vocabulary that lets the relevant facts be recorded and read consistently. Career-stage terms are, in this sense, equity infrastructure.

    Recording the mentorship relationship itself

    Beyond the CV, there is the question of recording the mentorship relationship as structured data. The vocabulary distinguishes a primary mentor from a secondary mentor, a thesis supervisor from a postdoc mentor, and records events such as mentee completion — a mentorship reaching a successful conclusion, a degree awarded, a postdoc transitioned to their next position. Where these are captured as structured records, with the people involved identified by ORCID iD, a mentorship history becomes something a researcher can carry with them, claim on a narrative CV, and have verified — rather than an unverifiable assertion.

    CRediT extensions and the limits of the current taxonomy

    How does CRediT handle this? Only partially, and that is a recognised gap. CRediT’s Supervision role covers “oversight and leadership responsibility… including mentorship external to the core team,” which captures mentorship that shapes a specific output. But CRediT applies to outputs, and most mentorship is not attached to a single paper. The doctoral supervision that shaped a researcher over four years is not well described by a Supervision tag on one of their papers.

    This is one of the motivations behind the active work on CRediT extensions and adjacent contribution vocabularies — roles for mentors, technical staff, and other acknowledged contributors whose work the 14-role taxonomy does not capture. The honest position is that mentorship is better served by the narrative CV and by structured relationship records than by stretching the output-level CRediT statement to cover it. CRediT credits contribution to a work; mentorship is contribution to a person, and the field is still building the vocabulary for the latter. Initiatives such as the Hidden REF have done much to make the case that this labour should be visible at all.

    What to do now

    For researchers: use the mentorship and career-development modules of narrative CV formats fully — describe the people you have developed, not just the papers you have produced. For institutions and funders: adopt a consistent career-stage vocabulary, record career breaks and fractional working, and make genuine career-stage adjustments in assessment. For vocabulary work: prioritise the structured representation of the mentorship relationship and the CRediT extensions for acknowledged contributors. The labour that builds the next generation of researchers should be visible in the record that generation inherits.

    Related reading

  • DORA, CoARA and narrative CVs: assessing research responsibly

    For a decade, “responsible research assessment” was mostly a matter of declarations — statements of principle that institutions signed and then struggled to operationalise. That has changed. Assessment reform has moved from declaration to practice, and anyone who now evaluates research or researchers — on a hiring panel, a promotion committee, or a grant board — is increasingly expected to do so by methods that the reform movement has made concrete. This article sets out how the three load-bearing pieces — DORA, CoARA, and the narrative CV — fit together, and what they ask of an evaluator. It draws on the responsible-assessment domain.

    DORA: the declaration that named the problem

    The Declaration on Research Assessment (DORA), issued in 2013, was the movement’s opening move. Its central target was the misuse of the journal impact factor as a proxy for the quality of individual papers and individual researchers. DORA’s argument was straightforward: a journal-level metric says nothing reliable about any single article published in that journal, and using it to judge a researcher’s work — for hiring, promotion, or funding — is a category error. DORA asked institutions, funders, and publishers to stop doing it, and to assess research on its own merits.

    DORA’s contribution was to name the problem clearly and to gather signatories — thousands of them — behind the principle. What it deliberately did not do was prescribe a detailed alternative. It was a declaration of what to stop, more than a manual for what to start. That left a gap, which the next decade’s work set out to fill.

    CoARA: from principle to coalition commitment

    The Coalition for Advancing Research Assessment (CoARA), launched in 2022, is the operational successor in spirit. Where DORA asked organisations to agree with a principle, CoARA asks members to commit to a reform agreement and to produce action plans for changing their own assessment practices. Its membership runs to hundreds of organisations — universities, funders, learned societies — across Europe and beyond.

    The shift from DORA to CoARA is the shift from “we endorse this” to “here is what we will change and by when.” CoARA’s commitments include recognising a diversity of research outputs and activities, basing assessment primarily on qualitative judgement supported by responsible use of metrics rather than the reverse, and abandoning inappropriate uses of journal- and publication-based metrics. It is, in effect, DORA’s principle turned into an implementation programme that members are accountable to.

    The narrative CV: the practical instrument

    If DORA named the problem and CoARA organised the commitment, the narrative CV is the instrument through which reform actually reaches an individual assessment. A narrative CV is a free-text format in which a researcher describes their contributions in prose, structured around a small set of prompts, rather than presenting an enumerated list of publications and metrics. The best-known implementation is UKRI’s Résumé for Research and Innovation (R4RI), which became standard across all UKRI funding from January 2024, building on the Royal Society’s earlier Résumé for Researchers. Wellcome, several other funders, and a number of institutions run their own variants.

    The narrative CV typically asks a researcher to describe their contributions across several dimensions — to the generation of knowledge, to the development of individuals, to the wider research community, and to broader society — rather than to list outputs by venue. The point is to make visible the contributions that a publication list renders invisible: mentorship, team building, peer review, open-science work, and the other forms of hidden labour that the Hidden REF initiative has campaigned to recognise. It is the mechanism by which a panel can assess a researcher as a contributor to research culture, not merely as a producer of papers.

    Responsible metrics, not no metrics

    A persistent misreading of this movement is that it is anti-metric. It is not. The principle, articulated in the Leiden Manifesto of 2015 and carried through CoARA, is responsible metrics: the principled use of quantitative indicators, always contextualised, always combined with qualitative expert judgement, never used as a substitute for reading the work. The objection is not to counting things; it is to letting a count — especially a journal-level one — stand in for judgement about an individual contribution. A responsible assessment may well use metrics; it simply refuses to let them do the assessing.

    How the three fit together

    The relationship is a progression from principle to practice. DORA supplies the foundational principle: do not mistake journal metrics for research quality. CoARA supplies the organised commitment and accountability: members agree to reform and publish how. The narrative CV supplies the concrete instrument: a format that forces an assessment to engage with what a researcher actually contributed. An evaluator working responsibly today is, in effect, applying DORA’s principle through CoARA-aligned practice using narrative-CV instruments.

    What responsible assessment asks of an evaluator

    Concretely, the movement asks an evaluator to read the work rather than its venue; to weigh a diversity of outputs — datasets, software, protocols, models — alongside articles, which presupposes a modern outputs taxonomy that recognises them; to use metrics only in support of judgement, never as a proxy for an individual’s worth; to recognise the hidden labour the narrative format is designed to surface; and to apply consistent qualitative criteria through a shared rubric, so that “narrative” does not become “unstructured and incomparable.”

    That last point is the live challenge. A narrative CV trades the false precision of metrics for the richer but less standardised evidence of prose, and prose is harder to compare across candidates. The answer is not to retreat to metrics but to develop shared rubrics so that narrative assessments are rigorous and fair rather than impressionistic.

    Where the dictionary fits

    Responsible assessment is awash with terms that every funder and institution defines slightly differently — narrative CV, contribution narrative, responsible metrics, hidden labour, team science. Without shared definitions, every reviewer reinvents their own rubric, which is exactly the inconsistency the movement is trying to escape. A shared, operational vocabulary for these concepts is what lets a narrative-CV reviewer at one institution mean the same thing as one at another. Providing that vocabulary — and pointing to DORA, CoARA, and UKRI for the normative content — is the convening role the CASRAI dictionary is built for. For a side-by-side account of the two frameworks, see our DORA versus CoARA comparison.

    What to do now

    For evaluators: read the work, use metrics only responsibly and in support of judgement, and engage seriously with the contributions a narrative CV surfaces. For institutions and funders: align practice with CoARA commitments and adopt narrative-CV formats with shared, qualitative rubrics so that assessments are comparable and fair. For standards work: define the responsible-assessment vocabulary operationally, federating to DORA, CoARA, and the funder narrative-CV guidance.

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