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Scientists at Major and Minor Universities: A Study of Productivity and Recognition
Abstract
Scientists at major schools are more likely to be productive and to win recognition than scientists at minor universities, which suggests that universities provide different environments for scientific research. Indices of productivity and recognition that differentiate between major and minor publications and major and minor honors were applied to the research careers of 150 scientists located at three universities of varying prestige. The best graduate schools select the best students, the best of whom are trained by top scientists and become the next generation's most productive scientists. Scientists trained and later hired by minor universities had difficulty developing continuity in their research activities and tended to be differently motivated than scientists trained and hired by major universities. In terms of his chances of obtaining recognition, a scientist gained more from affiliation with a major university than from high productivity or from his sponsor's prestige, probably because the major university provided better opportunities for contacts with eminent scientists in the same discipline.
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Cited by
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Almeida, P., & Kogut, B. (1999) · Management Science · doi:10.1287/mnsc.45.7.905 · Cited by 2,565
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Sine, W. D., Shane, S., & Gregorio, D. D. (2003) · Management Science · doi:10.1287/mnsc.49.4.478.14416 · Cited by 330
Metadata
- Authors
- Crane, D.
- Venue
- American Sociological Review
- Publisher
- SAGE Publications
- Published
- 1965-10
- Volume
- 30
- Issue
- 5
- Pages
- 699
- ISSN
- 0003-1224 (ISSN-L)
- OpenAlex
- W2325470334
- Cited by
- 502
- References
- 0
- FWCI
- 2.01
- Type
- journal article
- Language
- en
- Open access
- closed
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- Crane, D. (1965). Scientists at Major and Minor Universities: A Study of Productivity and Recognition. American Sociological Review. https://doi.org/10.2307/2091138
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.