Duplicate publication and ‘paper inflation’ in the fractals literature

Kostoff, Ronald N.; Johnson, Dustin; Río, J. A. del; Bloomfield, L. A.; Shlesinger, Michael F.; Malpohl, Guido; Cortés, Héctor D.

doi:10.1007/s11948-006-0052-5

Cited by 13 publications

(8 citation statements)

References 30 publications

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“…Finally, the number of articles is influenced by the database used, and says nothing about their impact [ 14 ]. Rewarding the publication of more papers regardless of impact may end up reinforcing bulk science, salami publication and least publishable unit practices [ 15 , 16 ].…”

Section: Resultsmentioning

confidence: 99%

International ranking systems for universities and institutions: a critical appraisal

Ioannidis

Patsopoulos

Kavvoura

et al. 2007

BMC Med

101

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Section: Resultsmentioning

confidence: 99%

International ranking systems for universities and institutions: a critical appraisal

Ioannidis

Patsopoulos

Kavvoura

et al. 2007

BMC Med

101

View full text Add to dashboard Cite

show abstract

“…Duplicate publication is a tangential issue to our work: Our aim is not to analyze republications, but we were aware of the phenomenon, since some of the self‐citations turned out to fall in that category, especially on the conference originals sample. Therefore, for the sake of completeness, we cursorily mention that studies on duplicate publication can be found mainly for medical sciences (von Elm, Poglia, Walder, & Tramer, ), but there is one study focusing on technological areas (Kostoff et al., ). Duplicate publishing generates an array of issues, like the inflation of some of the indices used for merit evaluation, not to mention the risk of copyright disputes, because often some of the authors are omitted in the republication, or the copyright of the original work belongs to the publisher.…”

Section: Related Researchmentioning

confidence: 99%

What happens to computer science research after it is published? Tracking CS research lines

Wainer

Valle

2013

J Am Soc Inf Sci Tec

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Are computer science papers extended after they are published? We have surveyed 200 computer science publications, 100 journal articles, and 100 conference papers, using self‐citations to identify potential and actual continuations. We are interested in determining the proportion of papers that do indeed continue, how and when the continuation takes place, and whether any distinctions are found between the journal and conference populations. Despite the implicit assumption of a research line behind each paper, manifest in the ubiquitous “future research” notes that close many of them, we find that more than 70% of the papers are never continued.

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“…Systematic gift authorship or other unsound practices for inflating CVs (e.g. salami publications [31]) would show themselves as more extensive networking in the indices that I propose. At the institutional level, excessive publications and mounting numbers of authors per paper similarly make an institution look larger in effective networking size and will decrease its adjusted scientific impact ( Q ).…”

Section: Discussionmentioning

confidence: 92%

Measuring Co-Authorship and Networking-Adjusted Scientific Impact

Ioannidis

2008

PLoS ONE

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Appraisal of the scientific impact of researchers, teams and institutions with productivity and citation metrics has major repercussions. Funding and promotion of individuals and survival of teams and institutions depend on publications and citations. In this competitive environment, the number of authors per paper is increasing and apparently some co-authors don't satisfy authorship criteria. Listing of individual contributions is still sporadic and also open to manipulation. Metrics are needed to measure the networking intensity for a single scientist or group of scientists accounting for patterns of co-authorship. Here, I define I1 for a single scientist as the number of authors who appear in at least I1 papers of the specific scientist. For a group of scientists or institution, In is defined as the number of authors who appear in at least In papers that bear the affiliation of the group or institution. I1 depends on the number of papers authored Np. The power exponent R of the relationship between I1 and Np categorizes scientists as solitary (R>2.5), nuclear (R = 2.25–2.5), networked (R = 2–2.25), extensively networked (R = 1.75–2) or collaborators (R<1.75). R may be used to adjust for co-authorship networking the citation impact of a scientist. In similarly provides a simple measure of the effective networking size to adjust the citation impact of groups or institutions. Empirical data are provided for single scientists and institutions for the proposed metrics. Cautious adoption of adjustments for co-authorship and networking in scientific appraisals may offer incentives for more accountable co-authorship behaviour in published articles.

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Duplicate publication and ‘paper inflation’ in the fractals literature

Cited by 13 publications

References 30 publications

International ranking systems for universities and institutions: a critical appraisal

International ranking systems for universities and institutions: a critical appraisal

What happens to computer science research after it is published? Tracking CS research lines

Measuring Co-Authorship and Networking-Adjusted Scientific Impact

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