by Daniel Bell
One is, in fact, immediately accessible. It depends on the seemingly reasonable assumption that the rate of further public acceptance of a new device or service will, at any time, be proportional to the extent to which the device or service is already used. To take a specific example, this assumption claims that the number of people who will buy and register automobiles, per unit time, will depend upon the extent of the opportunity for those who do not own cars to ride in a car that is owned by someone else. The extent of this opportunity will be proportional to the number of automobiles that are already registered.
23 Richard Stone, “A Model of the Educational System,” in Mathematics in the Social Sciences and Other Essays (Cambridge, 1966), esp. p. 105.
24 Derek Price, Science Since Babylon, pp. 115–116.
25 Derek Price, Big Science, Little Science (New York, 1963), pp. 23–25.
26 Ibid., p. 30.
27 Gerald Holton, “Scientific Research and Scholarship: Notes Toward the Design of Proper Scales,” Daedalus (Spring 1962), pp. 362–399. In this discussion of branching, I have largely followed Holton’s account.
28 Ibid., pp. 386–387.
29 Jean Fourastié, The Causes of Wealth (Glencoe, III., 1960), chap. I, esp. pp. 30–31.
30 For an elaboration of this point, see Daniel Bell, “The Disjunction of Culture and Social Structure,” in Gerald Holton, ed., Science and Culture (Boston, 1965), pp. 236–251.
31 As Ricardo wrote in his Principles of Political Economy and Taxation: “With a population pressing against the means of subsistence, the only remedies are either a reduction of people or a more rapid accumulation of capital. In rich countries, where all the fertile land is already cultivated, the latter remedy is neither very practicable nor very desirable, because its effect would be, if pushed very far, to render all classes equally poor.” Cited in Lester B. Lave, Technological Change: Its Conception and Measurement (Englewood Cliffs, N.J., 1966), p. 3. In the paragraph above, I have followed Lave’s formulations.
For Mill’s discussion of the stationary state, see Principles of Political Economy (Toronto, 1965), book IV, chap. 6, pp. 752–758.
32 Lave, op. cit.
33 Robert M. Solow, “Technical Change and the Aggregate Production Function,” Review of Economics and Statistics, vol. 39 (August 1957).
In his analysis, Solow postulated technology as a residual factor, after the computation of capital and labor inputs. But economists like to account for everything in terms of costs, and often do not like residual factors as explanations. Jorgenson and Griliches, accordingly, sought to recompute the data to show that changes in labor and capital inputs could account for the entire productivity increase. They write: “In explaining economic growth, we suggest greater reliance than heretofore on the twin pillars of human and nonhuman capital, each supporting an important part of the capital structure. Perhaps the day is not far off when economists can remove the intellectual scaffolding of technical change altogether.” See Zvi Griliches and D. W. Jorgenson, “Sources of Measured Productivity Changes: Capital Input,” American Economic Review (May 1960).
If the “right wing” questions the meaning of technology, the “left wing” argues that Solow’s framework is too neo-classical and pays insufficient attention to structural factors. In her analysis of production functions, Joan Robinson has been more interested in the capitalist framework as the setting which dictates the choice of techniques in production, rather than the general conditions of equilibrium. For a review of those issues, see G. C. Harcourt, “Some Cambridge Controversies in the Theory of Capital,” The Journal of Economic Literature, vol. VII, no. 2 (June 1969).
34 The definition here is based on the paper “Technological Change: Measurement Determinants and Diffusion,” by Edwin Mansfield, prepared for the National Commission on Technology, Automation and Economic Progress, and published in Appendix 1 to the report of the Commission, Technology and the American Economy (Washington, D.C., 1966).
35 Richard R. Nelson, Merton J. Peck, and Edward D. Kalachek, in their interesting book Technology, Economic Growth and Public Policy, The Brookings Institution (Washington, D.C., 1967), present a more disaggregated theory of a production function for technological progress. Seeking to designate the kinds and quantities of research-and-development inputs needed to make a design idea operational, they argue that the quantity of resources required depends on three key variables: (1) the magnitude of the advance sought over existing comparable products; (2) the nature of the product field, in particular the size and complexity of the system; and (3) the stock of relevant knowledge that permits new techniques to be derived or deduced, as well as the stock of available materials and components with which designers can work (p. 23).
36 Recalculations of Solow’s model disclosed some errors, and the share of capital in increasing productivity should have been 19 percent, not 12½ percent. See Lave, op. cit., p. 34.
37 John Kendrick, Productivity Trends in the United States, National Bureau of Economic Research and Princeton University Press (Princeton, N.J., 1961).
38 Robert M. Solow, “Investment and Technical Change,” in Mathematical Models in the Social Sciences, ed. Kenneth J. Arrow, Samuel Karlin, and Patrick Suppes (Stanford, 1959).
39Technology and the American Economy, p. 2.
40 The data are cited in Mansfield, “Technological Change,” op. cit., p. 105.
41Technology and the American Economy, p. 1. The words in brackets are from page 4 of the report. The Commission attributed the high unemployment rate of the period 1958–1966 to a low growth rate in the economy, as a result of a lagging aggregate demand, and the doubling of the entry rates of youths into the labor force, as the “baby boom” of the post-World War II period began to reach a crest.
Since some of the conclusions of the Commission’s report may be subject to challenge, it is prudent to “declare one’s interest.” I was a member of the Commission, participated in the studies, and signed the conclusions. The principal drafter of the sections on the pace of technological change was Professor Robert M. Solow of Massachusetts Institute of Technology.
42 See John Stuart Mill, Principles of Political Economy (New York, 1886), vol. II, book IV, chap. 6. As Mill says, so appealingly:
I cannot ... regard the stationary state of capital and wealth with the unaffected aversion so generally manifested towards it by political economists of the old school. I am inclined to believe that it would be, on the whole, a very considerable improvement on our present condition. I confess I am not charmed with the ideal of life held out by those who think that the normal state of human beings is that of struggling to get on; that the trampling, crushing, elbowing and treading on each other’s heels, which form the existing type of social life, are the most desirable lot of human kind, or anything but the disagreeable symptoms of one of the phases of industrial progress. It may be a necessary stage in the progress of civilization, and those European nations which have hitherto been so fortunate as to be preserved from it, may have it yet to undergo (p. 328).
43 Alvin Hansen, fiscal Policy and Business Cycles (New York, 1941).
44 Joseph Schumpeter, Capitalism, Socialism and Democracy (New York, 1942), pp. 117–118.
45 Nelson, Peck, and Kalachek, Technology, Economic Growth and Public Policy, op. cit., p. 41.
46 Ibid., p. 43 italics added.
47 J. J. Spengler, Presidential Address, American Economic Review (May 1966).
48 Erich Jantsch, Technological Forecasting in Perspective, Organization for Economic Cooperation and Development (Paris, 1967), p. 109.
49 Arthur C. Clarke, The Promise of Space (New York, 1968).
50 Theodor von Karman, Towards New Horizons, report submitted on behalf of the U.S. Air Force Scientific Advisory Group (November 7, 1944).
51 James Brian Quinn, “Technological Forecasting,” Harvard Business Review (April 1967).
52 R. C. Lenz, Jr., Technological Forecasting, Air Force Systems Command (June 1962).<
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53 I follow here largely the work of Robert Ayres and have drawn upon a number of memoranda he has prepared for the Hudson Institute.
54 Donald Schon, “Forecasting and Technological Forecasting,” in Toward the Year 2000: Work in Progress, ed. Daniel Bell (Boston, 1068).
55 If in forecasting parameters, one seeks to reduce the margin of error for particular techniques by grouping the “microvariables” into larger classes of relationships, there is the logical problem of classification: one may be arbitrarily selecting items to put together because they form a neat curve. The effort here to simplify may only distort. Most models, to be useful—and one sees this in economics —are highly cumbersome, involving hundreds of variables and equations. And yet this complexity is necessary if the predictions are to have a meaningful purchase on reality.
56 The exposition of the Delphi technique, as well as the results of the Rand study, are contained in Olaf Helmer, Social Technology (New York, 1966).
57 Erich Jantsch, Technological Forecasting, op. cit., p. 175.
58 Ibid., p. 176.
59 Ibid., pp. 178-180.
60 C. W. Churchman, R. L. Ackoff, and E. L. Arnoff, Introduction to Operations Research (New York, 1957).
61 Paul Samuelson, Problems of the American Economy (New York, 1962).
62 See, Technology and the American Economy, op. cit., Appendix 1.
63 Everett M. Rogers, Diffusion of Innovations (Glencoe, III., 1962).
64 Edwin Mansfield, Econometrica (October 1961)
65 Robert M. Solow, “Investment and Technical Change,” op. cit.
66 Edward Denison, Sources of Economic Growth, Committee on Economic Development (New York, 1962).
67 Fritz Machlup, op. cit., pp. 360-361. The figures on the proportion of educational expenditures to GNP are from the U.S. Government, Digest of Educational Statistics (U.S. Government Printing Office, 1970), p. 21.
68 Clark Kerr, The Uses of the University (New York, 1966).
69 In the sections that follow, all statistical data have been checked against available sources, and the latest year given is the one available as of mid-1972.
70 Abraham Moles, “La Cité Scientific dans 1972,” Futuribles (Paris, 1964).
71 These figures and projections, and those that follow for the subclassifications, are taken from “America’s Industrial and Occupational Manpower Requirements, 1964-1975,” prepared by the Bureau of Labor Statistics for the National Commission on Technology, Automation and Economic Progress, and printed in the appendix to Technology and the American Economy. Later projections issued in Tomorrow’s Manpower Needs, Bulletin 1606 (February 1969), modify these projections only fractionally.
72Review of National Science Policy: United States, Organisation for Economic Co-operation and Development (Paris, 1968), pp. 44-45, and U.S. Bureau of Labor Statistics, Bulletin 1606, ibid.
73 The statistical material in this section is drawn principally from two reports: the OECD Review of Science Policies; and American Science Manpower 1966, A Report of the National Register of Scientific and Technical Personnel, National Science Foundation NSF 68-7 (Washington, DC, 1968) supplemented by updated statistics from the U.S. Office of Education.
74 The 1970 census data will not be available until after 1972. Where updating has been possible for partial series, the text and tables reflect this.
75 By 1970., the figures had not changed significantly other than a shift to greater magnitudes in the proportion engaged in pharmaceuticals and instruments. NSF projections to 1975 indicate that 18.5 percent would be in pharmaceuticals and almost 26 percent in instruments.
76 Robert Heilbroner, The Limits of American Capitalism (New York, 1966), pp. 114-120, 150-132.
77 U.S. Department of Labor, Manpower Report of the President (Washington, D.C., 1967), p. 44.
78 Dael Wolfle and Charles V. Kidd, “The Future Market for Ph.D.’s,” Science, vol. 173 (August 27, 1971), pp. 784-793.
79 Allan M. Cartter, “Scientific Manpower for 1970-1985,” Science, vol. 172
80 Wallace R. Brode, “Manpower in Science and Engineering, Based on a Saturation Model,” Science, vol. 173 (July 16, 1971, pp. 206-213; citation from pp. 208-209.
81 The 18-21 age group is nor a completely reliable guide for purposes of projection, since about 33 percent of the present college and university students fall outside this range. According to the i960 census, the age distribution of undergraduates was as follows:
Under 18 18-21 22-24 25-29 30 and over
2.2% 67.7% 13.9% 11.2% 5.0%
Yet for comparative purposes, over time, we use the 18-21 age group as a “convention.”
82 Allan M. Cartter and Robert Farrell, “Higher Education in the Last Third of the Century,” The Educational Record (Spring, 1965), p. 121.
83 Alice Rivlin, “The Demand for Higher Education,” in Microanalysis of Socio-Economic Systems (New York, 1961), p. 216; cited by Folger, op. cit., p. 144.
84 Martin Trow, “The Democratization of Higher Education in America,” European Journal of Sociology, vol. III, no. 2 (1962), p. 255. John K. Folger, Helen S. Austin, and Alan E. Bayer, Human Resources and Advanced Education, Russell Sage Foundation (1970), pp. 2,21-322.
85 John Porter, “The Future of Upward Mobility,” American Sociological Review, vol. 33, no. 1 (February 1968), pp. 12-13.
86 Martin Trow, op. cit., pp. 255-256.
87 Alan Pifer, “Toward a Coherent Set of National Policies for Higher Education,” address to the Association of American Colleges (January 16, 1968).
88Digest of Educational Statistics, 1966, U.S. Office of Education (Washington, D.C., 1966), table 99, p. 78.
89 The first ten, in order, are: University of California (combined), Massachusetts institute of Technology, Columbia, University of Michigan, Harvard, University of linois, Stanford, University of Chicago, Minnesota, and Cornell.
The others, not in order are Yale, Princeton. Pennsylvania, North Carolina, Wis-onsin, Michigan State, Ohio State, New York University, California Institute of Technology, Rochester, and Washington.
90 See Daniel Bell, The Reforming of the General Education (New York, 1966), chap. 3.
91 Christopher Jencks and David Reisman, The Academic Revolution (New York, 1968), p. 272. In 1970, the private colleges and universities enrolled less than 30 percent of all students.
92 OECD, Reviews of National Science Policy: United States, p. 29.
93 The statistical data in this section, unless otherwise noted, have been taken from reports of the National Science Foundation, National Patterns of R & D Resources, Funds & Manpower in the United States (NSF 67-7); and Federal Funds for Research, Development and Other Scientific Activities, fiscal years 1966, 1967, and 1968, vol. XVI (NSF 67-19). Statistics dealing with the 1967-1970 period are from further NSF reports in the series and are cited in text.
94 The proportion of public funds in other countries is considerably lower. In 1964, according to the OECD, it was:
Country Percentage
France 63.3
United Kingdom 56.6
Sweden 47.7
Germany 40.4
Netherlands 40.0
Japan 27.8
Italy 33.1
95 A useful set of questions along this line is posed by Michel D. Reagan, “Basic and Applied Research: A Meaningful Distinction,” Science (March 17, 1967).
96 A comprehensive effort to provide a conceptual framework in sociological terms for this new, different kind of society has been made by Amitai Etzioni in The Active Society (New York, 1968). Pointing out, quite accurately, that the historic language and received models of sociology, even when emphasizing process, lack a vocabulary to deal with direction and choice, he has attempted the task of providing a scaffolding for new sociological structures. What I find contradictory about Etzioni’s effort is his employment of consciousness and cybernetics as his key terms. A cybernetic model, even though involving feedback and self-adjustment, is essentially mechanical an
d closed. Consciousness, and the implication of the enlargement of human vision and control over nature and society, can only operate in an open system.
97 A more sophisticated version of this argument is made by Robert Lane in his essay, “The Decline of Politics and Ideology in a Knowledgeable Society,” American Sociological Review (October 1966).
98 This technocratic dream in such writers as Saint-Simon, Cournot, F. W. Taylor, and Veblen, and its limitations in a politicalized world are discussed in chap. 6.
99 See the symposium on “The Financing of Higher Education,” in The Public Interest, no. 11 (Spring 1968), with contributions by Clark Kerr, David Truman, Martin Meyerson, Charles Hitch, et al.
100 See Daniel Bell, The Reforming of General Education; and Jerome Bruner, The Process of Education (Cambridge, Mass., 1960).
101 This question is discussed in chap. 5, on the idea of a social report.
1 All the data are from the Statistical Abstract of the United States (1971).
2 E. V. Rostow, “To Whom and for What. Ends is Corporate Management Responsible,” in The Corporation in Modern Society, ed. Edward S. Mason (Cambridge, Mass., 1959), p. 59.
3 The stereotype that the big company has a big market share is obviously supported by many examples. Only it is refuted by even more. If one looks at the “symbolic” examples of concentration, it is quite clear that in no industry today is concentration at a comparable level with the period after the great wave of consolidations, from 1898 to 1002. As pointed out by Professor Segall of the University of Chicago: In 1900, International Harvester produced 85 percent of the nation’s harvesting machines. In 1902, National Biscuit controlled 70 percent of the biscuit output. In 1901, American Can turned out 90 percent of its industry’s output. In 1902, Corn Products had 80 percent of its industry’s capacity. In 1902, U.S. Leather accounted for more than 60 percent of leather output; Distillers Securities provided more than 60 percent of whiskey output; International Paper produced 60 percent of all newsprint. In 1900, American Sugar Refining refined virtually all the sugar in the country. For a comprehensive discussion of the contemporary degree of concentration see M. A. Adelman, “The Two Faces of Economic Concentration,” The Public Interest, no. 21 (Fall 1970).