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Science policy researchers and scientists themselves know reflexively that differences among scientific fields matter. However, sets of government-sponsored science and engineering (S&E) indicators are quite general and in most instances do not report differences among fields. We evaluate the current limitations of S&E indicators, identifying particular data needs about scientific fields. We suggest developing a disaggregated, flexible S&E classification. We argue that disaggregating S&E indicators through faceted analysis or webbed or networked databases will enable users to account for specialization, interdisciplinarity and emerging fields, and to adapt the S&E indicators across databases, making indicators more useful for international comparison.
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Feeney et al. (2005) studied this question.
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