Lost in publication: how measurement harms science
By P. Lawrence. 2008
136 citations recorded by the source corpus.
Measurement of scientific productivity is difficult. The measures used (impact factor of the journal, citations to the paper being measured) are crude. But these measures are now so univer- sally adopted that they determine most things that matter: tenure or unemployment, a postdoctoral grant or none, success or failure. As a result, scientists have been forced to downgrade their primary aim from making discoveries to publishing as many papers as possible — and trying to work them into high impact factor journals. Consequently, scientific behaviour has become distorted and the utility, quality and objectivity of articles has deteriorated. Changes to the way scientists are assessed are urgently needed, and I suggest some here.
Subfields: Ecological Modeling, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/e271cd4788322e14c44ffb46b5c6d225bf558e37
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In Ecological Modeling
In Statistics and Probability
Citations in the corpus
- Towards a taxonomy of research misconduct: The case of business school research (2019, background): “(2007) stress, research proxies are often oversimplified, failing to capture important paths of knowledge flow; hence, a preoccupation with readily available proxies can result in counterproductive activities, where the proxies become the de facto goals of institutions or individuals (see also Zimme”
- Deep impact: unintended consequences of journal rank (2013, background): “We have reviewed the pertinent empirical literature to supplement the largely argumentative discussion on the opinion pages of many learned journals [12,54,81,85,90,96–105] with empirical data.”