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| Content Provider | World Health Organization (WHO)-Global Index Medicus |
|---|---|
| Author | Fawcett, Tim W. Higginson, Andrew D. |
| Description | Author Affiliation: Fawcett TW ( School of Biological Sciences, University of Bristol, Bristol BS8 1UG, United Kingdom. tim.fawcett@cantab.net); |
| Abstract | Most research in biology is empirical, yet empirical studies rely fundamentally on theoretical work for generating testable predictions and interpreting observations. Despite this interdependence, many empirical studies build largely on other empirical studies with little direct reference to relevant theory, suggesting a failure of communication that may hinder scientific progress. To investigate the extent of this problem, we analyzed how the use of mathematical equations affects the scientific impact of studies in ecology and evolution. The density of equations in an article has a significant negative impact on citation rates, with papers receiving 28% fewer citations overall for each additional equation per page in the main text. Long, equation-dense papers tend to be more frequently cited by other theoretical papers, but this increase is outweighed by a sharp drop in citations from nontheoretical papers (35% fewer citations for each additional equation per page in the main text). In contrast, equations presented in an accompanying appendix do not lessen a paper's impact. Our analysis suggests possible strategies for enhancing the presentation of mathematical models to facilitate progress in disciplines that rely on the tight integration of theoretical and empirical work. |
| ISSN | 00278424 |
| e-ISSN | 10916490 |
| Journal | Proceedings of the National Academy of Sciences of the United States of America |
| Issue Number | 29 |
| Volume Number | 109 |
| Language | English |
| Publisher | National Academy of Sciences |
| Publisher Date | 2012-07-01 |
| Publisher Place | United States |
| Access Restriction | Open |
| Subject Keyword | Biological Evolution Communication Barriers Ecology Information Dissemination Mathematics Journal Impact Factor Models, Statistical Research Support, Non-U.S. Gov't Multidisciplinary |
| Content Type | Text |
| Resource Type | Article |
| Subject | Multidisciplinary |
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