TY - JOUR
T1 - Metrics and mechanisms
T2 - Measuring the unmeasurable in the science of science
AU - Wu, Lingfei
AU - Kittur, Aniket
AU - Youn, Hyejin
AU - Milojevic, Staša
AU - Leahey, Erin
AU - Fiore, Stephen M.
AU - Ahn, Yong Yeol
N1 - Publisher Copyright:
© 2022 Elsevier Ltd.
PY - 2022/5
Y1 - 2022/5
N2 - What science does, what science could do, and how to make science work? If we want to know the answers to these questions, we need to be able to uncover the mechanisms of science, going beyond metrics that are easily collectible and quantifiable. In this perspective piece, we link metrics to mechanisms by demonstrating how emerging metrics of science not only offer complementaries to existing ones, but also shed light on the hidden structure and mechanisms of science. Based on fundamental properties of science, we classify existing theories and findings into: hot and cold science referring to attention shift between scientific fields, fast and slow science reflecting productivity of scientists and teams, soft and hard science revealing reproducibility of scientific research. We suggest that interest about mechanisms of science since Derek J. de Solla Price, Robert K. Merton, Eugene Garfield, and many others complement the zeitgeist in pursuing new, complex metrics without understanding the underlying processes. We propose that understanding and modeling the mechanisms of science condition effective development and application of metrics.
AB - What science does, what science could do, and how to make science work? If we want to know the answers to these questions, we need to be able to uncover the mechanisms of science, going beyond metrics that are easily collectible and quantifiable. In this perspective piece, we link metrics to mechanisms by demonstrating how emerging metrics of science not only offer complementaries to existing ones, but also shed light on the hidden structure and mechanisms of science. Based on fundamental properties of science, we classify existing theories and findings into: hot and cold science referring to attention shift between scientific fields, fast and slow science reflecting productivity of scientists and teams, soft and hard science revealing reproducibility of scientific research. We suggest that interest about mechanisms of science since Derek J. de Solla Price, Robert K. Merton, Eugene Garfield, and many others complement the zeitgeist in pursuing new, complex metrics without understanding the underlying processes. We propose that understanding and modeling the mechanisms of science condition effective development and application of metrics.
KW - 68T50
KW - 91D30
KW - Citation
KW - Measure
KW - Novelty 2021 MSC: 68U35
KW - Science of science
UR - http://www.scopus.com/inward/record.url?scp=85130222507&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85130222507&partnerID=8YFLogxK
U2 - 10.1016/j.joi.2022.101290
DO - 10.1016/j.joi.2022.101290
M3 - Article
AN - SCOPUS:85130222507
SN - 1751-1577
VL - 16
JO - Journal of Informetrics
JF - Journal of Informetrics
IS - 2
M1 - 101290
ER -