CASRAI Dictionary

Tag: research culture

  • 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

  • Responsible conduct of research: training, culture and the integrity ecosystem

    It is tempting to imagine that research integrity is secured by rules: define misconduct clearly enough, publish the policy, and trust will follow. But anyone who has worked in research knows that the hardest integrity questions are rarely about clear-cut fabrication or plagiarism. They are about the grey areas — how to handle an awkward result, who deserves to be an author, what to do about a supervisor’s expectations, how much detail to report. These are resolved less by rulebooks than by the training researchers receive, the culture of the environments they work in, and the institutions that support good practice and respond when it fails. Together these form an integrity ecosystem. This article examines that ecosystem — responsible conduct of research training, research culture, and the bodies that uphold integrity — drawing on the research integrity domain of the CASRAI Dictionary.

    Beyond the binary of misconduct

    Research integrity is often framed around its most serious violations — fabrication, falsification and plagiarism — and those are rightly treated as gravely wrong. But focusing only on the extremes misses where most integrity is actually won or lost. Far more common, and far more corrosive in aggregate, are the everyday questionable practices: selective reporting of results, inappropriate authorship, sloppy record-keeping, inadequate description of methods, the small compromises made under pressure. These rarely trigger a formal investigation, yet they undermine the reliability of the literature just as surely. A mature view of integrity, therefore, is not merely about catching the worst behaviour but about cultivating the everyday good practice that prevents the slide toward it. That is fundamentally a matter of training and culture, not enforcement alone.

    Responsible conduct of research training

    Responsible conduct of research (RCR) training is the educational component of the ecosystem: structured instruction in the principles and practices of doing research well. Good RCR training goes well beyond reciting the definitions of misconduct. It covers the design and management of data, the responsible use of methods, the norms of authorship and contributorship, the handling of conflicts of interest, the ethics of working with human participants and animals, mentoring relationships, peer review, and how to navigate the genuine dilemmas that arise in practice. Its purpose is formative rather than merely cautionary: to help researchers internalise good practice as a professional habit, and to give them the vocabulary and confidence to recognise and discuss integrity questions before they become problems. Training works best early and repeatedly, woven through a research career rather than delivered once as a compliance exercise.

    Research culture: the environment that shapes behaviour

    Training has limited effect in a hostile environment. The single most powerful determinant of whether researchers act with integrity is the culture around them — the incentives, pressures, examples and norms of their immediate setting. A culture that rewards quantity over quality, that prizes positive results, that tolerates exploitative mentoring, or that punishes the admission of error, will undermine the best training. A culture that values careful work, supports the reporting of negative or null results, models good authorship practice, and makes it safe to raise concerns will reinforce it. Much of the recent attention to research integrity has accordingly shifted toward research culture — recognising that you cannot train your way out of an environment whose incentives push in the wrong direction. Changing culture is slower and harder than running a course, but it is where the deepest gains lie.

    The institutions of the integrity ecosystem

    Surrounding training and culture are the bodies that set expectations, offer guidance and respond to allegations. These operate at different levels and play complementary roles:

    • National oversight and policy bodies establish standards and, in some systems, handle allegations involving publicly funded research. In the United States, for example, the Office of Research Integrity (ORI) oversees integrity in research funded through its remit.
    • National advisory and support organisations promote good practice and offer guidance to institutions and researchers. In the United Kingdom, the UK Research Integrity Office (UKRIO) provides independent, confidential advice and education on research integrity.
    • Institutions themselves carry the front-line responsibility: providing training, fostering culture, maintaining policies, and investigating concerns fairly when they arise.
    • Journals, publishers and editorial bodies uphold integrity at the point of publication, through editorial policies, correction and retraction processes, and shared community guidance.

    No single layer is sufficient alone. The strength of the ecosystem comes from their overlap: training informs culture, culture is reinforced by institutional expectations, and oversight bodies provide both standards to aspire to and a backstop when prevention fails.

    Where integrity meets everyday practice

    The integrity ecosystem is most visible not in dramatic misconduct cases but in the ordinary disputes it helps prevent and resolve. Authorship is the classic example: disagreements over who should be named, in what order, and on what basis are among the most common and most damaging integrity problems in everyday research life, and they are best handled through clear norms, transparent contribution practices and, where needed, fair institutional processes — the subject of our guidance on resolving authorship disputes. Many such disputes never arise at all when contribution is recorded honestly and explicitly from the outset. Structured contributorship through the CRediT taxonomy — whose roles are described in our overview of the CRediT roles — supports integrity in exactly this way, by making who-did-what a matter of explicit record rather than later contention.

    A shared language for integrity

    Integrity training, culture and oversight all depend on people meaning the same things by the same terms — what counts as authorship, what constitutes a conflict of interest, what a particular contribution amounts to. When those terms drift between institutions, training schemes and policies, the ecosystem fractures. A consistent vocabulary keeps it coherent, which is what the CASRAI Dictionary provides: shared definitions so that the concepts at the heart of responsible conduct are understood the same way across the training, the culture and the institutions that together make research trustworthy.

  • Recognising technicians and research-support staff: the Technician Commitment

    Walk into almost any laboratory, imaging suite, sequencing facility or data centre that produces research, and you will find people whose names rarely appear in the papers that result. Technicians keep instruments calibrated and running; facility managers maintain the shared equipment that whole departments depend on; data stewards organise and preserve the records that make analysis possible; and a wide range of research-support staff provide the specialist expertise without which the work would simply stop. Their contribution is foundational, and it is frequently invisible. The conventional reward systems of academia — authorship, citation, the publication record — were built around a narrower idea of who does research, and they often leave support staff out. This article looks at efforts to change that, drawing on the mentorship and career-stages domain of the CASRAI Dictionary.

    The recognition problem

    The problem is partly structural. Recognition in research has long been organised around the published article and its byline, and around metrics derived from it. Someone whose contribution is essential but does not fit the authorship mould — who built and maintained the instrument rather than designing the study, who curated the data rather than interpreting it, who ran a shared facility used by dozens of projects — can find that there is no obvious place for them in the formal record. The result is a career landscape in which support staff may be indispensable yet under-recognised: harder to promote on the basis of contribution, harder to retain when their work is invisible, and easy to overlook when funding and credit are distributed. This is not merely unfair to individuals; it weakens the research enterprise, because skilled technical staff who feel unrecognised are exactly the people research can least afford to lose.

    The Technician Commitment

    One of the most prominent responses is the Technician Commitment, an initiative through which research organisations pledge to address the visibility, recognition, career development and sustainability of their technical staff. The commitment is built around several themes. Visibility calls for ensuring technicians and their contributions are recognised within institutions and in research outputs. Recognition and career development addresses the need for clear progression routes, professional development and proper standing for technical roles. Sustainability concerns securing the future of the technical skills base on which research depends. By signing, organisations make public commitments and report on their progress, turning good intentions into accountable action. The Technician Commitment matters because it names the problem at an institutional level and asks employers, not just individuals, to do something about it.

    Making support contributions visible in outputs

    Institutional commitments matter, but recognition also has to reach into the outputs themselves, where so much credit is anchored. Several mechanisms help:

    • Contributorship statements. Moving from a bare author list to a structured statement of who did what creates room to name and describe contributions — technical and supporting work included — that a byline alone would hide.
    • Authorship where warranted. Where a technician’s contribution meets the criteria for authorship, including them as an author is the most direct form of recognition, and contribution-based thinking makes that case easier to see.
    • Crediting data and software work. When the data a facility produces, or the software a research engineer builds, is published as a citable output, the people responsible can be recognised as creators and contributors in its own right.
    • Specific acknowledgement. Where a contribution does not rise to authorship, a precise acknowledgement that states what someone did is far more meaningful than a generic line of thanks.

    How CRediT helps

    A contribution-based view of recognition depends on having a shared way to describe contributions, and this is where the CRediT taxonomy is particularly useful for support staff. Several of its roles map directly onto the work technicians and research-support staff do: Investigation for conducting experiments and operating instruments, Data curation for managing, annotating and maintaining data, Resources for providing materials, instruments and facilities, and Software for those who build the tools. The full set of roles is set out in our overview of the CRediT roles. By describing contributions in these terms, a contributorship statement can record exactly what a technician did, in the same structured vocabulary used for every other contributor — which means their work appears in the formal record as contribution, not as an afterthought. That parity of description is itself a form of recognition: it places technical work on the same footing as the work that has always been visible.

    Recognition across the career

    Recognition is not only about individual papers; it is about careers. Technical and support roles are genuine research careers with their own trajectories, and recognising them properly means attending to progression, development and standing over time — the concerns of the mentorship and career-stages domain. When contributions are visible in the record, they can inform promotion and reward; when career structures acknowledge technical expertise, skilled people are more likely to stay and develop. Visibility in outputs and visibility in careers reinforce one another.

    A consistent record of who contributes

    For the contributions of technicians and support staff to be recognised consistently — across institutions, publishers and reporting systems — the way those contributions are described must mean the same thing everywhere. That consistency is what the CASRAI Dictionary provides: a shared vocabulary so that the work of a technician, a data steward or a facility manager is understood and credited the same way wherever it is recorded. The Technician Commitment asks institutions to value the people who keep research running; a shared vocabulary for contribution helps ensure that value is reflected, honestly and visibly, in the record itself.

  • Responsible research assessment in hiring and promotion

    Few decisions shape a research career more than those made at the moment of hiring, tenure and promotion. They determine who enters the profession, who advances, and whose work is rewarded — and in doing so they send a powerful signal about what the system values. For decades, those decisions have leaned heavily on a familiar set of shortcuts: the prestige of the journals a researcher has published in, the impact factor attached to those journals, the raw count of their publications, and the citations they have accumulated. These proxies are seductive because they are quick and appear objective. But a growing movement argues they are also distorting — rewarding the wrong things, overlooking much of what researchers genuinely contribute, and shaping behaviour in ways that harm research itself. This article examines the reform of assessment in hiring and promotion, drawing on the responsible-assessment domain of the CASRAI Dictionary.

    What the metric-driven approach gets wrong

    The case against journal-based and citation-based assessment is not that numbers are useless but that they are being asked to do work they cannot do. The journal impact factor is a measure of a journal’s average citation performance; it says nothing reliable about the quality or significance of any individual article within it, still less about the researcher who wrote it. Using it to judge people is a category error. Citation counts, meanwhile, are slow, field-dependent and easily distorted, and they capture only one narrow kind of influence. More corrosively, when careers depend on these proxies, researchers are pushed to chase them — prioritising quantity, fashionable topics, more papers, and venues where the metrics are favourable. The metric stops measuring behaviour and starts driving it, and much of what research needs — rigorous replication, careful data curation, mentoring, software, public engagement — goes unrewarded because it does not show up in the count.

    DORA and the founding principle

    The reform movement’s most influential starting point is the San Francisco Declaration on Research Assessment (DORA). Its central recommendation is simple and far-reaching: do not use journal-based metrics, such as the impact factor, as a surrogate measure of the quality of individual research articles or of the contributions of individual researchers in hiring, promotion and funding decisions. Instead, DORA urges that research be assessed on its own merits and that the full range of research outputs and activities be valued. Thousands of organisations and individuals have signed, committing to change how they evaluate. DORA’s power lies in naming the central abuse plainly and asking institutions to stop it — making the misuse of the impact factor something an organisation must publicly disavow rather than quietly perpetuate.

    The Leiden Manifesto and the Hong Kong Principles

    Other frameworks complement DORA. The Leiden Manifesto sets out principles for the responsible use of metrics — that quantitative evaluation should support, not supplant, expert qualitative judgement; that measurement be aligned with the mission of institution and researcher; that data and analysis be open and verifiable; and that indicators account for variation by field. It does not reject metrics but disciplines them. The Hong Kong Principles focus on assessing researchers in ways that reward trustworthy research — recognising open, rigorous and reproducible practices and the full range of research activities — so that assessment pulls towards integrity rather than against it. Together these frameworks describe an assessment system that uses judgement supported by responsible indicators, rather than indicators in place of judgement.

    CoARA and the move from declaration to action

    The most ambitious recent development is the Coalition for Advancing Research Assessment (CoARA) and its Agreement on Reforming Research Assessment. CoARA moves the conversation from principle to implementation: signatory organisations commit to concrete reform, including basing assessment primarily on qualitative judgement supported by responsible use of quantitative indicators, recognising the diversity of research outputs and activities, and abandoning the inappropriate use of journal- and publication-based metrics. Crucially, CoARA asks organisations to actually change their criteria and processes — their hiring rubrics, their promotion frameworks — and to share progress, turning broad agreement into the difficult, practical work of rewriting the rules by which careers are judged.

    The narrative CV as a practical instrument

    If institutions are to stop counting papers and start assessing contribution, they need a different way of presenting a career — and the narrative CV has become the leading answer. Instead of a long list of outputs and metrics, a narrative CV asks researchers to describe their contributions in prose: what they have contributed to the generation of knowledge, to the research community, to wider society, and to the people and teams they have worked with. This format makes space for exactly the things metrics miss — mentoring, data and software, collaboration, public engagement, contributions to research culture — and it invites qualitative peer judgement of substance rather than mechanical comparison of numbers. The narrative CV is not a panacea; it must be assessed fairly and consistently. But it embodies the reform agenda in a single document: it asks what someone did and why it mattered, rather than where and how often they published.

    Contribution, vocabulary and fair judgement

    Assessing contribution fairly depends on being able to describe contributions clearly and consistently. This is where structured accounts of who did what become valuable: the CRediT taxonomy, whose full set of contribution types is set out in our overview of the CRediT roles, lets a researcher’s actual role in their work be stated rather than inferred from a byline — supporting the kind of contribution-based assessment these reforms call for, and connecting naturally to the wider conduct of authorship and contributorship. For assessment to be fair across institutions and systems, the terms used to describe outputs, roles and contributions must mean the same thing everywhere; that consistency is what the CASRAI Dictionary provides. Reforming assessment is ultimately about realigning reward with worth — ensuring that the people who do the most valuable research, in all its forms, are the people the system recognises and advances.

  • Reforming research culture: institutional change beyond the metrics debate

    Much of the conversation about responsible research assessment has, understandably, focused on metrics: the over-reliance on journal impact factors, the misuse of citation counts, the distorting effect of ranking people by where they publish rather than by what they contribute. These are real problems, and reforming how research is measured is genuinely important. But there is a risk in framing the whole challenge as a debate about metrics, because it can make the task look smaller than it is. Replacing one set of numbers with another, or adding a narrative section to an application form, does not by itself change the culture of research — the web of incentives, behaviours, relationships and rewards that actually shapes how people do their work. This article looks at the broader project of reforming research culture, drawing on the responsible assessment domain of the CASRAI Dictionary.

    Why culture, not just metrics

    Research culture is the environment in which research happens: how people are hired, promoted and rewarded; whether collaboration, mentorship and openness are valued or merely tolerated; whether the pressure to produce flashy results crowds out the slow, careful, reproducible work that good science depends on. Metrics are part of this culture, but only part. A system can adopt enlightened assessment criteria on paper while still, in practice, rewarding the same narrow behaviours, because the underlying incentives, expectations and norms have not shifted. Genuine reform means attending to the whole environment, not just the measurement layer on top of it. The metrics debate is the visible tip; the culture is the larger mass beneath.

    Wellcome and the research-culture agenda

    One of the organisations that has done most to widen this conversation is Wellcome, whose work on research culture has drawn attention to the lived experience of researchers and the pressures that shape it. Wellcome’s research-culture programme has highlighted that the environment in which research is conducted — the competitiveness, the precarity of careers, the toll on wellbeing — is itself a determinant of research quality and integrity. The insight is that you cannot reliably get good, honest, careful research out of a culture that rewards the opposite. By framing research culture as worthy of serious attention in its own right, this work has moved the conversation beyond the technicalities of assessment towards the human realities that assessment exists to serve.

    The Hong Kong Principles

    If the goal is to reward the behaviours that make research trustworthy, then assessment needs to be aligned with research integrity — and this is precisely what the Hong Kong Principles for assessing researchers set out to do. The Hong Kong Principles propose that researchers should be assessed in ways that recognise and reward trustworthy research practices: responsible research conduct, transparent reporting that includes the full record rather than only positive results, open science, a diversity of contributions and roles, and the activities that build and sustain the research community. Their distinctive contribution is to connect assessment directly to integrity: instead of asking only “how productive or highly cited is this researcher?”, they ask “does this researcher do their work in a trustworthy, open and responsible way?” This reframes assessment as a lever for better behaviour, not merely a measurement exercise — if institutions reward the practices that make research reliable, they get more of them.

    CoARA and institutional commitment

    Principles need vehicles for action, and one of the most significant is the Coalition for Advancing Research Assessment (CoARA). CoARA brings together organisations that commit to reforming research assessment, and crucially it asks them to make concrete commitments and to develop action plans for change within their own institutions. This institutional dimension is what distinguishes durable reform from good intentions. It is one thing for an individual to believe assessment should be broader and more responsible; it is another for a university or funder to commit publicly, develop a plan, and hold itself accountable for changing its own practices. By moving reform from the level of individual conviction to the level of institutional commitment, CoARA helps ensure that cultural change is embedded in how organisations actually operate, rather than remaining an aspiration that never reaches the committee rooms where decisions are made.

    Recognising diverse contributions and reproducible work

    A recurring theme across all of these efforts is the recognition of a broader range of contributions and the valuing of careful, reproducible practice. Several strands matter:

    • Diverse contributions. Research depends on far more than first-author papers — on data and software, on mentorship, on peer review, on technical and supporting work, on building shared resources. A reformed culture finds ways to recognise these.
    • Reproducibility. Valuing rigorous, transparent, reproducible work — rather than only novel or eye-catching results — is central to a healthier culture, because reproducibility is the foundation of reliable knowledge.
    • Openness. Rewarding open practices — open data, open methods, open access — aligns incentives with the kind of transparent research the community says it wants.

    From assessment to culture, and back

    Assessment and culture are bound together. How we assess researchers signals what we value, and what we value shapes how people behave. The structured description of contributions plays a role here: when a person’s full range of contributions can be recorded and recognised — through frameworks such as the CRediT taxonomy and its set of contribution roles — it becomes possible to value more than the narrow signals that metrics capture. But the description is a means, not an end. The end is a research culture in which good, honest, open, careful, collaborative work is genuinely rewarded, and in which the people who do it can build sustainable careers.

    A shared vocabulary for a shared reform

    Reforming culture across many institutions requires a common language for what is being recognised and valued. Contribution types, assessment criteria and the elements of a researcher’s record must be described consistently, or reform in one place cannot be understood or built upon elsewhere. That consistency is what the CASRAI Dictionary supports: a shared vocabulary for describing the contributions and activities that a reformed culture seeks to reward. The metrics debate opened the door; the larger work — the one Wellcome, the Hong Kong Principles and CoARA are pursuing — is changing the culture the metrics were only ever a symptom of.