Do citations and impact factors relate to the real numbers in publications? A case study of citation rates, impact, and effect sizes in ecology and evolutionary biology

Christopher J. Lortie (), Lonnie W. Aarssen, Amber E. Budden and Roosa Leimu
Additional contact information
Christopher J. Lortie: York University
Lonnie W. Aarssen: Queen’s University
Amber E. Budden: National Centre for Ecological Analysis and Synthesis
Roosa Leimu: University of Oxford

Scientometrics, 2013, vol. 94, issue 2, No 13, 675-682

Abstract: Abstract Metrics of success or impact in academia may do more harm than good. To explore the value of citations, the reported efficacy of treatments in ecology and evolution from close to 1,500 publications was examined. If citation behavior is rationale, i.e. studies that successfully applied a treatment and detected greater biological effects are cited more frequently, then we predict that larger effect sizes increases study relative citation rates. This prediction was not supported. Citations are likely thus a poor proxy for the quantitative merit of a given treatment in ecology and evolutionary biology—unlike evidence-based medicine wherein the success of a drug or treatment on human health is one of the critical attributes. Impact factor of the journal is a broader metric, as one would expect, but it also unrelated to the mean effect sizes for the respective populations of publications. The interpretation by the authors of the treatment effects within each study differed depending on whether the hypothesis was supported or rejected. Significantly larger effect sizes were associated with rejection of a hypothesis. This suggests that only the most rigorous studies reporting negative results are published or that authors set a higher burden of proof in rejecting a hypothesis. The former is likely true to a major extent since only 29 % of the studies rejected the hypotheses tested. These findings indicate that the use of citations to identify important papers in this specific discipline—at least in terms of designing a new experiment or contrasting treatments—is of limited value.

Keywords: Citations; Ecology; Effect size; Evolutionary biology; Hypothesis testing; Treatments (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://link.springer.com/10.1007/s11192-012-0822-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:scient:v:94:y:2013:i:2:d:10.1007_s11192-012-0822-6

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11192

DOI: 10.1007/s11192-012-0822-6

Access Statistics for this article

Scientometrics is currently edited by Wolfgang Glänzel

More articles in Scientometrics from Springer, Akadémiai Kiadó
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().