|
|
|
|
| LEADER |
01396nmm a2200229 u 4500 |
| 001 |
EB002099793 |
| 003 |
EBX01000000000000001239883 |
| 005 |
00000000000000.0 |
| 007 |
cr||||||||||||||||||||| |
| 008 |
221013 ||| eng |
| 100 |
1 |
|
|a Wagstaff, Adam
|
| 245 |
0 |
0 |
|a On Measuring Scientific Influence
|h Elektronische Ressource
|c Wagstaff, Adam
|
| 260 |
|
|
|a Washington, D.C
|b The World Bank
|c 2010
|
| 300 |
|
|
|a 22 p
|
| 700 |
1 |
|
|a Wagstaff, Adam
|
| 700 |
1 |
|
|a Ravallion, Martin
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
|
| 989 |
|
|
|b WOBA
|a World Bank E-Library Archive
|
| 028 |
5 |
0 |
|a 10.1596/1813-9450-5375
|
| 856 |
4 |
0 |
|u http://elibrary.worldbank.org/doi/book/10.1596/1813-9450-5375
|x Verlag
|3 Volltext
|
| 082 |
0 |
|
|a 330
|
| 520 |
|
|
|a Bibliometric measures based on citations are widely used in assessing the scientific publication records of authors, institutions and journals. Yet currently favored measures lack a clear conceptual foundation and are known to have counter-intuitive properties. The authors propose a new approach that is grounded on a theoretical "influence function," representing explicit prior beliefs about how citations reflect influence. They provide conditions for robust qualitative comparisons of influence - conditions that can be implemented using readily-available data. An example is provided using the economics publication records of selected universities and the World Bank
|