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Quantitative Assessments of the Physical and Mathematical Sciences A Summary of the Lessons Learned (1994) / Chapter Skim
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Addititional Issues on Conducting Quantitative Assessments
Pages 10-12

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From page 10...
... If long-term scientific directions that have been motivated by sound historical and philosophical imperatives are neglected as a result of mass gravitation toward funding opportunities, the intellectual vigor of the discipline may in fact be questionable. Thus any interpretation of numerical metrics of adaptability must take into account value judgments of the sort indicated above.
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From page 11...
... A quantitative approach to studying a discipline also requires adequate funding to cover the requisite expertise and additional staff time. If the analysis relies solely on existing data sources, the costs will be significantly less than if it includes the collection of new data through a statistical sampling, a formal survey, or the purchase of customized data runs from commercial data sources.
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From page 12...
... In addition, even the data with some degree of detail presented significant difficulties. For instance, the best available database on science and engineering personnel, the two OSEP surveys, has subcategories for atomic and molecular physics and for optics, but both subcategories are listed under physics only, although a substantial amount of the research in AMO science is more properly categorized under chemistry or engineering.
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Key Terms

  • engineering personnel
  • adequate funding
  • quantitative assessments
  • requisite expertise
  • amo science

  • diverse data
  • significant limitation
  • analysis relies
  • substantial amount
  • readily accessible

  • commercial data
  • typical nrc
  • staff time
  • planning purposes
  • categories chosen

  • retrospective analyses
  • periodic adjustments
  • time lag
  • valid lead
  • available positions

  • funding opportunities
  • defined fields
  • job register
  • necessarily representative
  • useful sources

  • consistent set
  • properly categorized
  • osep surveys
  • formal survey
  • labor statistics


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