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Manpower Forecasters as Lobbyists: A Case Study of the Working Group on Manpower Parameters for Scientific Growth 1965–8

  • Kevin McCormick

Abstract

For the past thirty years public discussion and official policy for scientific and technological manpower in Britain has been punctuated by announcements of brave hopes and bleak disenchantment about the possibilities of using forecasting techniques to guide educational policy. The machinery of advice developed in the postwar reconstruction was largely discredited and even disowned by some of its members by the beginning of the 1960s. Yet a vigorous burst of officially-appointed forecasting activity was undertaken in the mid-1960s. By the end of the decade these official platforms had been dismantled and many of the forecasters confessed disappointment over their efforts. Another flare-up of forecasting activity appeared likely in the mid-1970s when the Minister of State for Higher Education poked among the embers and announced the necessity for manpower forecasting to guide education. On this occasion, however, no official bodies were established and the smouldering desire to use the educational system to promote economic reform awaits a new champion. Meanwhile the cycle of official resolve and retraction requires some explanation. At the present time, there is widespread disenchantment with the conceptual tools of manpower forecasting, disenchantment about the possibility of translating forecasts into effective policy recommendations, and disenchantment with the educational system as a promoter of social change. In this essay I shall attempt to unravel some of these strands of enthusiasm and subsequent disenchantment by a case study of one manpower forecasting body in the mid-1960s-the Working Group on Manpower Parameters for Scientific Growth.1

Keywords

Working Group Educational System Scientific Policy Interim Report Forecast Activity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Notes

  1. 2.
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Copyright information

© Science Policy Research Unit, Sussex 1979

Authors and Affiliations

  • Kevin McCormick

There are no affiliations available

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