Antecedents and Near-Term Consequences for Interdisciplinary Dissertators

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Kniffin, Kevin M.;Hanks, Drew

Description

Given the complexity of questions studied by academicians, institutions are increasingly encouraging interdisciplinary research to tackle these problems; however, neither the individual-level pathways leading to the pursuit of interdisciplinary research nor the resulting market outcomes have been closely examined. In this study, we focus attention on the individuals who complete interdisciplinary dissertations to ask “who are they and how do they fare after earning the PhD?” Since interdisciplinary research is known to be relatively risky among academics, we examine demographic variables that are known to be associated in other contexts with risk-taking before considering whether interdisciplinarians’ outcomes are different upon graduating. First among our three main findings, students whose fathers earned a college degree demonstrated a 1.2% higher probability of pursuing interdisciplinary research. Second, the probability that non-citizens pursue interdisciplinary dissertation work is 4.7% higher when compared with US citizens. Third, individuals who complete an interdisciplinary dissertation tend to earn approximately 2% less in the year after graduation; however, mediation analyses show that the decision to become a postdoctoral researcher accounts for the apparent salary penalty. Our findings shed light on the antecedents and near-term consequences for individuals who complete interdisciplinary dissertations and contribute to broader policy debates concerning supports for academic career paths. DOI: 10.1007/s11192-017-2317-y Keywords: Interdisciplinary Research; Wages; Risk; Immigrants *** Information on requesting the 2010 SED Data is online at . *** Sending an initial email to is among the first steps that is required.

Citations (2)

Mentions (0)

Metrics

Dataset Index

1.0

FAIR Score

92%

Citations

2

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

Scientometrics

Assigned Domain

Subfield

Artificial Intelligence

Field

Computer Science

Domain

Physical Sciences

Confidence Score

63%

Source

Scholar Data Model

Keywords

Interdisciplinary ResearchWagesRiskImmigrants

Normalization Factors

FT

13.46

CTw

1.00

MTw

1.00