CASRAI Dictionary

Tag: self-citation rate

  • Limitations of Bibliometrics: DORA and CoARA

    Bibliometrics — the statistical analysis of publication and citation data — cannot reliably stand in for research quality on its own: field-specific citation practices, author self-citation, and outright metric gaming all distort single-number scores such as the h-index or Journal Impact Factor. This is the documented evidentiary basis for DORA and CoARA’s push to replace single-score evaluation with qualitative, multi-indicator assessment.

    Bibliometrics is the quantitative study of academic literature — citation counts, publication volume, and derived indices — used as a proxy for scholarly influence. The proxy breaks down whenever a single number is asked to carry the full weight of a quality judgement, which is precisely what large-scale hiring, promotion, tenure, and funding panels have done for decades.

    What is bibliometrics, and why does one score fall short?

    Bibliometric indicators — citation counts, the h-index, the Journal Impact Factor (JIF), and derived composite scores — were built for large-scale, aggregate comparisons, not for judging an individual scholar’s contribution. Bergstrom, West and Wiseman’s 2008 analysis in the Journal of Neuroscience put it plainly: quantitative metrics are poor choices for assessing an individual’s research output compared with the “gold standard” of reading the work and consulting domain experts.

    A single score compresses conflicting dimensions of scholarly value — novelty, rigour, reproducibility, societal reach — into one figure. That compression, not citation data itself, is the structural weakness reform movements target.

    How does field bias distort bibliometric comparisons?

    Citation practices vary sharply by discipline, so raw citation counts cannot be compared across fields. Mathematics and the humanities publish and cite far less frequently than biomedicine, and books and conference proceedings — the dominant outputs in many humanities and computing sub-fields — are tracked inconsistently, or not at all, by Web of Science and Scopus.

    Coverage gaps compound the bias. Indexing databases differ in subject breadth, subject depth, geographic coverage, language coverage, and how far back citation histories extend, so researchers publishing outside the Anglophone, journal-dominant core of a database are systematically under-counted. Belter’s 2015 review in PMC also notes that citation-based indicators require roughly two to three years after publication before they stabilise enough to be considered reliable — a lag that penalises early-career researchers and recent work by design.

    Why does self-citation inflate bibliometric scores?

    Self-citation — an author citing their own prior work — is a normal and often legitimate part of building on a research programme. It becomes a distortion when it is used strategically to inflate an individual’s citation count or a journal’s Impact Factor beyond what independent uptake of the work would justify.

    Clarivate’s Journal Citation Reports has, in past cycles, suppressed the calculated Impact Factor of titles found to display anomalous citation behaviour, including excessive journal self-citation and coordinated “citation stacking” arrangements between journals — a documented, database-level enforcement action against exactly this failure mode. At author level, unusually concentrated self-citation rates are one of the diagnostic flags bibliometricians use when auditing whether a headline citation figure reflects genuine external uptake or engineered inflation.

    Does field-weighted citation impact solve the problem?

    Field-weighted citation impact (FWCI) is a normalised metric — used in tools such as Scopus/SciVal — that adjusts a publication’s citation count against the average for its subject field, publication year, and document type, so that a score of 1.0 represents “as expected” performance for that context. It is a genuine improvement on raw citation counts because it corrects for the field-bias problem described above.

    FWCI does not, however, correct for self-citation gaming or database coverage gaps, and it remains a single number: it shows how a paper performed against a benchmark, not whether the research was rigorous or original. Reform frameworks treat field normalisation as a refinement of bibliometrics, not a licence to keep using any single indicator as a proxy for quality.

    What evidence underlies DORA and CoARA’s reform case?

    The San Francisco Declaration on Research Assessment (DORA), launched in 2012, explicitly recommends against using the Journal Impact Factor as a surrogate measure of the quality of individual research articles, and calls on institutions to assess research on its own merits using a range of qualitative and quantitative indicators. The Coalition for Advancing Research Assessment (CoARA), formed in 2022, builds on DORA’s diagnosis: its signatories commit to basing assessment primarily on qualitative, peer-reviewed judgement, supported by responsible — not exclusive — use of quantitative indicators, and to abandoning inappropriate use of journal- and publication-based metrics such as the JIF and h-index.

    Both build directly on the failure modes above: field bias, self-citation gaming, database coverage gaps, and the two-to-three-year reliability lag are the documented evidence, not abstract principle, behind the push for reform.

    Initiative Launched Core commitment
    DORA (San Francisco Declaration on Research Assessment) 2012 Stop using the Journal Impact Factor as a proxy for individual article or researcher quality
    Leiden Manifesto 2015 (Hicks et al., Nature 520, 429–431) Ten principles for the responsible, transparent use of quantitative indicators alongside expert judgement
    CoARA (Coalition for Advancing Research Assessment) 2022 Base assessment primarily on qualitative peer review; abandon inappropriate JIF/h-index use in hiring, promotion and funding decisions

    Answer-first questions on bibliometric limitations

    What are the main limitations of bibliometrics in research assessment?

    The main limitations are field bias (citation norms differ by discipline), database coverage gaps (books, non-English and non-journal outputs are under-tracked), self-citation inflation, and a two-to-three-year lag before citation counts stabilise. Together these mean a single score cannot substitute for expert, qualitative judgement of research quality.

    Why is the h-index considered a poor measure of individual research quality?

    The h-index rewards volume and career length over insight, cannot distinguish a highly cited author from a member of a large collaborative team, and does not account for field-specific citation norms. Bergstrom, West and Wiseman (2008) concluded that reading the work and consulting experts remains the more reliable standard for individual evaluation.

    What is the difference between DORA and CoARA?

    DORA (2012) is a signable declaration focused primarily on eliminating Journal Impact Factor misuse. CoARA (2022) is a membership coalition of funders, universities and academies that goes further, committing signatories to a broader, peer-review-centred reform agenda across hiring, promotion, and institutional evaluation, with periodic reporting on progress.

    What is a self-citation rate and why does it matter?

    A self-citation rate is the proportion of an author’s or journal’s total citations that come from their own prior work rather than independent external uptake. Bibliometricians and citation-database auditors (including Clarivate’s Journal Citation Reports process) use unusually high self-citation rates as a flag for possible metric gaming rather than genuine scholarly influence.

    What should research administrators do differently?

    For research administrators and institutional leaders, the practical implication is not to discard citation data but to stop letting any single figure carry a hiring, promotion, or funding decision unsupervised. That means:

    • Pairing field-normalised indicators such as FWCI with narrative, qualitative peer assessment, as CoARA commitments require.
    • Auditing self-citation and journal self-citation patterns before citing a headline figure in a case file.
    • Recognising a fuller range of outputs — datasets, software, policy influence — rather than journal articles alone.
    • Crediting individual contributions on multi-author papers explicitly, rather than inferring credit from author position or aggregate citation share.

    On that last point, standardised contributor-role taxonomies address a related gap directly. CASRAI originated the CRediT contributor role taxonomy in 2014; the standard is now stewarded by NISO as ANSI/NISO Z39.104-2022, and it lets institutions record which named contributor performed which specific role on a paper — conceptualisation, data curation, writing — rather than relying on citation share or author-list position as a proxy for who did what.

    Where bibliometric reform goes next

    The evidentiary case against single-number bibliometric scores is now well established: field bias, database coverage gaps, self-citation gaming, and a multi-year reliability lag are documented, auditable failure modes, not theoretical objections. DORA and CoARA translate that evidence into institutional commitments, and field-normalised metrics such as FWCI narrow — without eliminating — the field-bias problem.

    The direction of travel for funders, universities and academies is toward layered assessment: responsibly used quantitative indicators, transparent contributor-role attribution, and peer judgement at the centre, rather than any one score standing alone.

  • Is Self-Citation Ethical in Responsible Metrics?

    Is self-citation ethical? Self-citation is ethical when an author cites their own prior work because it is genuinely relevant to a new argument, method, or dataset; it becomes unethical only when the primary motive shifts to inflating citation counts, h-index, or a journal’s impact factor. Neither DORA nor CoARA — the two dominant responsible-metrics frameworks — sets a self-citation rule, leaving this judgement almost entirely to editors, reviewers, and individual conscience.

    Self-citation is the practice of an author referencing their own previously published work within a new publication, most commonly to establish methodological continuity, avoid self-plagiarism, or trace the development of a research programme over time.

    What counts as self-citation, and why do researchers do it?

    Self-citation occurs whenever an author lists their own prior publication in a new paper’s reference list. It is neither rare nor inherently suspect: most research is cumulative, and a study that builds on a researcher’s earlier method, dataset, or theoretical framework has good reason to cite that earlier work directly.

    • Establishing methodological continuity with a previously validated technique or instrument
    • Avoiding self-plagiarism by properly attributing earlier text, data, or ideas
    • Tracing the trajectory of a multi-paper research programme for the reader
    • Providing background the author is best placed to cite because they generated the original finding

    The Committee on Publication Ethics (COPE) has noted that failing to cite one’s own directly relevant prior work can itself mislead readers into thinking a study is more novel than it is — so the ethical failure mode runs in both directions, not only toward over-citation.

    How much self-citation is considered excessive?

    There is no single, universally agreed self-citation rate ceiling. A 2023 analysis published in PMC concluded that a self-citation rate around 20 percent is conservatively tolerable for individual researchers, with rates substantially above that treated as inappropriate — but the same paper stresses that discipline size and publication norms shift what counts as normal.

    COPE’s own November 2017 forum discussion, “Self-Citation: Where’s the Line?”, found no consensus figure among editors. Some journals cap the absolute number of self-citations (for example, no more than five), others use a percentage-of-total-references ceiling, and many rely on case-by-case editorial judgement rather than a fixed rule. COPE’s broader position on handling citation manipulation asks journals to set their own thresholds and educate authors, rather than prescribing one number for the whole of scholarly publishing.

    A 2025 analysis in the Journal of Academic Ethics (Springer) reinforces the intent-based test over a rate-based one, concluding that “ethical reviewers should avoid unnecessary self-citation” while allowing that citing one’s own work is acceptable “if directly relevant” — the same relevance-over-frequency logic COPE applies.

    Why don’t DORA and CoARA address self-citation directly?

    The San Francisco Declaration on Research Assessment (DORA, 2012) is aimed squarely at eliminating the use of the journal impact factor as a proxy for individual researcher quality in hiring, funding, and promotion decisions. It says nothing about how many times an author may cite themselves within a paper’s reference list — that is a citation-practice question, not a journal-metric question, and sits outside DORA’s original scope.

    The Coalition for Advancing Research Assessment (CoARA), formed in 2022, commits signatory institutions to move away from inappropriate use of quantitative indicators and toward qualitative, narrative-based evaluation. This is the closest thing academia has to a responsible-metrics consensus position, yet CoARA’s Agreement likewise does not name self-citation as a distinct risk category — it addresses metric misuse at the institutional and assessment level, not individual reference-list behaviour.

    The result is a genuine governance gap. Self-citation sits between two policy domains — publication ethics (COPE’s territory) and research assessment reform (DORA and CoARA’s territory) — without either treating it as a first-class concern. Editors are left applying inconsistent journal-level rules, while institutional assessment reformers focus almost entirely on how metrics are used rather than on what feeds into them.

    Disclosure norms vs blanket caps: the better governance model

    A blanket percentage cap on self-citation is easy to state but poorly matched to how research actually varies. Small or emerging subfields with few active authors, first-in-series methodology papers, and long-running research programmes will all show naturally higher self-citation rates than a large, well-established field — penalising a rate rather than the intent behind it risks punishing legitimate continuity while doing little to stop a determined metric-gamer, who can simply keep self-citations just under whatever line is drawn.

    A more workable precedent already exists in bibliometrics. The standardized citation-metrics database maintained by Ioannidis, Boyack, and Baas — used to identify the world’s most-cited scientists across disciplines — reports each author’s composite citation score both with and without self-citations included, alongside their raw self-citation percentage. It does not impose a cutoff; it makes the number visible and lets the reader judge. That is a disclosure model, not a cap.

    Framework Year Position on self-citation Governance model
    COPE 2017/ongoing Case-by-case editorial judgement; no fixed universal threshold Journal-level policy, editorial discretion
    DORA 2012 Not addressed; targets impact-factor misuse in assessment Institutional assessment reform
    CoARA 2022 Not addressed; targets inappropriate metric use generally Institutional assessment reform
    Ioannidis/Boyack/Baas database 2019, updated annually Reports self-citation rate transparently alongside adjusted score Disclosure, no cap
    Individual journal caps Varies Fixed number or percentage limit on self-citations Blunt rule, inconsistently applied

    Applying that same logic to individual authors and grant applicants is straightforward: require a disclosed self-citation rate alongside any citation-based metric submitted for hiring, promotion, or funding decisions, rather than an arbitrary cap that cannot distinguish a legitimate methods lineage from deliberate metric inflation.

    Answer-first Q&A on self-citation ethics

    Is self-citation unethical?

    Self-citation is not inherently unethical. It becomes ethically problematic only when it is used to inflate citation metrics rather than to serve genuine scholarly continuity — what COPE treats as a form of citation manipulation. Relevance to the argument, not frequency, is the ethical test that matters.

    Is it okay to cite yourself in a research paper?

    Yes. Citing your own prior work is standard practice when it establishes methodological continuity, avoids self-plagiarism, or shows how a study builds on earlier findings. Problems arise only when self-citations serve no argumentative purpose beyond raising an author’s h-index or a journal’s impact factor.

    Is self-citation illegal?

    No. Self-citation is a matter of publication ethics, not law. Excessive or irrelevant self-citation can breach a journal’s editorial policy or COPE’s citation-manipulation guidance, potentially triggering a correction or editorial inquiry, but it carries no legal liability in any jurisdiction.

    Implications for journals, funders, and institutions

    Journals can adopt the disclosure model directly: require authors to report a manuscript’s self-citation percentage at submission, alongside a one-line rationale where the rate is unusually high, rather than enforcing an arbitrary cap during peer review.

    CoARA signatories reforming promotion and funding criteria are well placed to extend their existing move toward narrative CVs by asking applicants to disclose self-citation-adjusted metrics alongside any citation count submitted for assessment — consistent with CoARA’s broader commitment to context over raw indicators.

    DORA signatories evaluating individual researchers already commit to judging research on its own merits rather than by journal-level proxies; adding a self-citation disclosure line to that practice would close a gap the original 2012 declaration was never designed to cover.

    Conclusion: toward transparent, not punitive, norms

    Self-citation is not a solved problem in responsible metrics guidance — it is an unaddressed one. DORA targets journal-level metric misuse; CoARA targets institutional assessment culture; COPE offers editorial case law without a universal rule. None of the three treats individual self-citation disclosure as a named requirement.

    The fix does not need a new blanket percentage cap, which would misfire across disciplines of different sizes and publication norms. It needs a disclosure norm: report the self-citation rate, report the rationale where it is high, and let editors, funders, and hiring committees judge intent with that information in hand — the same logic that already underpins the field’s most credible standardized citation databases.