Area of Research: The Scientific Enterprise

The proletariat of American research, the graduate students and the postdocs, cry and whisper. Internet traffic even suggests they organize. At Yale, some struck. Meanwhile, William Massy of Stanford University and Charles Goldman of RAND Corp. present a fresh analysis to explain the doctoral system (W.F. Massy, C.A. Goldman, The Production and Utilization of Science and Engineering Doctorates in the United States, Stanford Institute for Higher Education Research, 1995), and the National Academy of Sciences (NAS) complex releases two major assessments of American graduate education and research (Reshaping the Graduate Education of Scientists and Engineers and Research-Doctorate Programs in the United States, NAS, Washington, D.C., 1995). The bottom line is that alma mater is doctoring too many children.

Malthus’s classic negative checks on population were famine, war, and ill health. Here I would like to provide a backdrop for considering more positive checks on the burgeoning number of Ph.D.’s, drawing in part on the facts and findings in the three 1995 studies. Five features dominate: expansion of degree-granting franchises; the forgotten origin of the expansion, a need for teachers; emergence of a research enterprise recruiting students to sustain itself; a star system for faculty, further tipping graduate schools toward research; and, finally, too many doctorates. My positive checks, like those of Malthus, will involve better understanding and purposeful action as well as moral restraint.

Franchise Expansion

The number and size of universities granting doctorates have multiplied. Gaining status, the institutions awarding a Ph.D. in science and engineering (S&E) doubled from 1961 to 1991, reaching 299. Grantors of master’s degrees in S&E slightly more than doubled in the same period, reaching 442, and provide a ready pool to multiply the population of schools granting Ph.D.’s still more.

No convincing logic defines the optimal set of doctoral programs for America. However, absolute numbers now impress in almost every field. In each major sub-field within biology, 100 to 200 schools now award Ph.D.’s. Circa 1990, 182 granted degrees in physics, 169 in mathematics, and 130 in civil engineering. Even in a sub-sub field such as biomedical engineering 86 granted Ph.D.’s, and in the sub-field of physics and biology called oceanography, 50 did so.

Enrollment multiplied as the franchises expanded. From 1967 to 1992, graduate students of all kinds increased about half, twice the growth of the United States population. They multiplied from slightly less than a half-million to just over two-thirds million. The swelling number of schools increased the annual output of S&E Ph.D.’s from about 18,000 to 25,000 during the decade 1983-93.

If a franchise means spending $30 million or more of federal money annually for basic research, about 100 institutions have franchises. In 1970 only about 30 universities had large research programs. (The 100 produce about 90 percent of Ph.D.’s.)

From 1960 to now, major league baseball added more franchises, too, from 16 to 28. The New York Yankees could not maintain their dynasty in that expanding field. The 1995 NAS ranking of doctoral programs in dozens of fields showed predictably that the average rank of most universities declined with the expanding number of competitors, worsening morale and lengthening the climb to the top of the standings. Questions also arise about the qualifications of a larger absolute number of students and faculty.

The Forgotten Need For Teachers

In the 1950s, war veterans swelled the ranks of students. Recovering from the thin years of the Depression, colleges needed teachers quickly. Fresh Ph.D.’s staffed the rapidly expanding state universities and enlarging older institutions, too. Subsequently, democratization of educational opportunity and the baby boom sustained the college boom.

Secondarily, the government paid for training technical personnel to compete with the perceived scientific prowess of the Soviets. With fresh memories of the victories of science in World War II and ample tax revenues, the government paid for research campaigns, even a war on cancer. These payments to spend more time on research encouraged professors to cut their hours of contact with students from, say, nine to three per week, tripling-in this example-the need for teachers (or teaching assistants).

Notwithstanding the college boom, the fraction of Ph.D.’s employed in academe declined from about 55 percent in 1973 to about 45 percent in 1991. The fraction whose primary work is teaching dropped from 36 percent in 1972 to 23 percent in 1991. Meanwhile, the fraction no longer performing research, the presumed goal of a Ph.D., or whose work was unclear, doubled to about one-third of those surveyed. When the investment in a degree totals $250,000, one wonders for these lost researchers whether doctoral training was a wise choice, for them or the nation.

Sustaining Research

By the 1980s, the demand for full-fledged teachers slowed, a large cadre of principal investigators was in place, and the research enterprise needed skilled workers. The market for Ph.D.’s no longer drove the production of Ph.D.’s but rather the need of the research enterprise for low-cost labor called graduate students and postdocs. The enterprise perfumes this reality by praising the effectiveness of joint education and research. Of course, no oppressive conspiracy existed. Rather, individual faculty and funders have acted rationally in their self-interest, heedless until recently of possibly harmful collective effects.

Objective understanding of doctoral production and use demystifies many current features of the system. These include the lengthening time to get a degree and the growing number of foreign students. Doctoral students and postdocs substitute for faculty in research. They also unburden faculty, more in the humanities and social sciences, in undergraduate teaching and evaluation. Expanding graduate enrollments and postdocs costs less than hiring new faculty. Moreover, faculty-especially young faculty-competing for promotion and eminence through research logically recruit yet more graduate students but lack an incentive to speed them to a degree.

Recruits to S&E face a dim future: six or seven years registered for a degree, eight or nine years from B.S. to Ph.D., then one or more postdocs, and thus no substantial income until past age 30. In the life sciences, for example, the Ph.D.’s age to a median of 33 years by the time they land their first permanent job.

American undergraduates with exceptional talent likely spy the opportunity costs posed by the long apprenticeship. Far superior incomes in other careers leave science attracting only those young Americans who hear a profound calling. In fact, the number of American male Ph.D.’s has shrunk for a quarter-century. Women and foreign students account for the growth. In many schools and fields, roughly half of graduate students and postdocs are foreign.

Foreign youth still know graduate training in America will propel them upward. Preferring to remain in the U.S., they may accept slow progression to the degree and a succession of low-paying postdocs. The practically infinite availability of young foreign talent could maintain the system as it exists, although politics, prosperity, and currencies cause fluctuations. Japan, Taiwan, Korea, and China send the most students. China, India, Malaysia, and Indonesia send particularly high fractions for engineering and science.

The Star System

Senior faculty have evolved a strategy of horizontally mobile stars, akin to “free agency” in baseball. The stars auction themselves to the highest bidder, driving up the cost of their services. Ratcheting up the top-most compensation packages, they restrict the dollars for expansion of the middle class of permanent faculty. The recent end to mandatory retirement at age 70 works in the same direction. At the same time the middle class is restricted, the enterprise tilts from teaching toward the research that brightens the stars.

The stars’ ambitions and tastes require not more undergraduates but more workers. Thus, institutions offer or accommodate more graduate students and postdocs as part of their bid for a star, and also hire more cheap adjunct teaching faculty to moderate the wage bill. The number and years of the postdocs expanded most dramatically in biology, where the fraction of postdocs so employed one to four years after an American Ph.D. first climbed rapidly during the 1970s and now hovers around 40 percent. As almost all fields boarded the bandwagon, the number of S&E postdocs tripled from about 8,000 in 1975 to 24,000 in 1992. The stars are well served.

Too Many Ph.D.’s

At the bottom line, one finds the “natural production rate” of Ph.D.’s in the American system based on the population of professors in doctorate programs and the total fertility rate of each professor. Physicist David Goodstein of the California Institute of Technology puts that fertility rate at about 15 Ph.D.’s per professorial career in fields he knows, while I guess the rate necessary for breeding professors to replace the national population of S&E Ph.D.’s is about five per career. The present outcome exceeds the steady-state intake of faculty into U.S. schools more than the demand from American industry and government and from abroad can absorb. Students stretch out their school years, partly because job prospects are poor, and partly because funders and peers of the discipline favor money for students or recruits. The life of the postdoc provides a further way to stretch the years, but even their numbers may be near saturation.

Persuasive recent findings by Massy and Goldman, funded by the New York-based Alfred P. Sloan Foundation, hint Ph.D.’s in engineering, math, and some sciences are currently overproduced fully 25 percent.

An expansion of universities or research could temporarily absorb the excess doctorates, but within a few years, sponsoring more university research would worsen Ph.D. job prospects in S&E. Immediate gains from faculty expansion would give way to more oversupply as expanded doctoral programs produce yet more graduates.

Challenges And Opportunities

Universities must reconsider production of Ph.D.’s and the invisible hands of franchise expansion, recruiting to sustain the enterprise, and stars that propel it. We should seek positive checks on population rather than suffer the academic equivalents of famine, war, and ill health.

The prescription must produce research without producing the disillusioned. During a period when money from research remains steady or falls, some universities might well revisit an antiquated system of staffing that makes durable commitments to technicians and shelters faculty who do not hold the high expectations of fresh Ph.D.’s and postdocs. Universities could reward students who finish fast, and penalize faculty whose students loiter.

Valorizing the master’s degree in sciences would reduce exploitation. In engineering, the master’s is respected and lucrative, while in scientific fields it is a stigmatized consolation. Consider students who look forward to careers in business or secondary schools, which might be where the elusive third of the Ph.D.’s went. For them, instead of a protracted and disillusioning Ph.D., an intensive two years of science courses after a B.S. program might meet their needs while benefiting the nation and reflecting glory instead of disenchantment on the university.

Another positive prescription is reducing the cost of research without a youthful army of exploited inductees minimizing labor cost. The late Yale historian of science Derek de Solla Price resignedly conjectured that scientific results grow at the discouraging price of the cube root of the expense (Little Science, Big Science . . . and Beyond, Columbia University Press, 1986). Cannot science find routes to increase its productivity, as other service industries now aggressively do? Surely, for example, scientists in America should spend more time doing research and less time proposing and reviewing.

Affection for alma mater and recognition of the invisible hands driving her causes several of us to try seriously to create “SimU.” Opportunities come from understanding the university as a system, in particular how the actors make their decisions. In more and more useful ways, simulation games raise questions about how agents behave and how the parts of a system interact. Such tools now simulate oil refineries and factories, the oceans and the atmosphere.

Maxis Software Inc. of Orinda, Calif., has created educational and commercially successful games, engagingly called SimEarth and SimCity. Seeking a learning tool for the many people and organizations concerned with the problems and solutions discussed here, experts in universities and simulations are beginning to create a virtual alma mater of Malthusian forces, invisible hands, and stakeholders. It may help universities manage better. The proletariat who cry and whisper on the Internet deserve at least this much.

Jesse H. Ausubel is director of the Program for the Human Environment at Rockefeller University and a program officer for the Alfred P. Sloan Foundation in New York, where he leads the foundation’s program on “The University as a System and the System of Universities.”(The Scientist, Vol:10, #3, pg.11 , February 5, 1996)(Copyright © The Scientist, Inc.)The Scientist, 3600 Market Street, Suite 450, Philadelphia, PA 19104, U.S.A.[This article appeared on The Scientist web page, used with permission – psm].

I write on the occasion of the publication of a special issue of the journal Technology in Society entitled “Scientists, War, and Diplomacy: European Perspectives.” [1] The issue arises from a joint project of the George C. Marshall Institute (Washington DC) and Futuribles International (Paris) on the role of scientific cooperation in improving relations between nations in conflict.

War, diplomacy, and Europe form a familiar trio, one that has dominated the study of history.  George Marshall supremely understood this trio.  General Marshall served as Chief of Staff of the US Army during World War II and later as Secretary of State.  In 1953 Marshall received the Nobel peace prize for his plans and accomplishments that established the recovery of Western Europe.

Novelty resides in adding scientists to the trio of war, diplomacy, and Europe, and their presence requires comment.

My comment begins with a definition of science.  Science is a system of communication for the control of complexity.  Control of complexity happens to be the central parameter of evolution.  Extremely long, error-free messages are needed for control.  DNA and RNA are life’s famously long messengers with minimal errors.  They dominated evolution for a couple of billion years, a domination a couple of million times longer than the Roman Empire.

More recently, humanity has nourished a competitor, or supplement, to DNA, namely science.  Scientific papers as well as engineering creations of various kinds may be considered attempts to create long, error-free, operational messages, transcending generations.  Operational means predictive.  The model or the machine works, just like the wing of a bird or the gene making a protein.

The bottom line is that the goal of science is power, and science becomes more powerful over time.  Twenty-three centuries ago, Archimedes’ commander-in-chief understood the power of science.  The generals of World War II, including Marshall, watched that conflict end with science’s biggest bang.  Society’s military and civilian leaders are accustomed to making use of science in war.

A by-product of the power of science is the power of its practitioners.  Realistically, the practitioners of science, scientists, retain little of the power they create.  Generals, politicians, and business managers seize most of it.  Still, scientists retain some, and hence acquire responsibilities and opportunities.

The excellent networks characteristic of science amplify the responsibilities and opportunities.  Science functions globally as a single club, with mathematics and computation as its lingua franca.  The strength of the international networks varies by discipline, greatest in physical sciences where the syntax is strictest and weakest in non-quantitative social sciences.  As the shooting stops, scientists find themselves networked both with the powerful elites of their own nation and with scientists in other nations.  So, individual scientists who wish to play a role in reduction of conflict or normalization of relations have chances to do so.

In fact, scientists have played surprisingly diverse and timely roles in improving relations between nations in conflict.  This special issue of Technology in Society, generously made possible by the editors of the journal, George Bugliarello and George Schillinger, firmly makes the case for Europe since World War II.  A 1998 volume, published by the New York Academy of Sciences with support from Carnegie Corporation of New York, explored scientists’ roles in the diplomacy between Israel and Egypt, Argentina and Brazil, and the U.S. and both the Soviet Union and China.[2]

If we believed conflict were at an end, the capacity identified would matter little.  Alas, humans are territorial animals, and conflicts abound even where expanses of land are no longer in dispute.  In fact, urbanized populations fight block by block.  The desire for control of territory is controlled by the most ancient part of the brain, the part humans share with snakes and other reptiles.

Here we must think of emergent Europe, the subject of a conference in Paris in February 2000 conducted as part of the joint project between Marshall and Futuribles.  Incidentally, the father of the director of Futuribles, Hugues de Jouvenel, was Bertrand de Jouvenel, author of the profound book, On Power, written in occupied France.[3]  The conference was the source and stimulus of the papers in “Scientists, War, and Diplomacy: European Perspectives”.  The papers, by authors who have distinguished themselves in science, in war, and in diplomacy, look both backward and forward.

One of the authors is the late William A. Nierenberg, a member of the Board of the Marshall Institute, accomplished physicist and oceanographer, and former assistant secretary general of NATO.  Bill, as well as Marshall Board members John Moore and Frederick Seitz, strongly encouraged this activity.  Bill’s paper is one of several in the volume, including those by Joseph Rovan and Alexander King, that offer candid, personal accounts of protagonists in cooperative activities.  The immediacy of their reports is complemented by the more detached assessments of such leading historians and social scientists as Hartmut Kaelble, Pierre Gremion, and Jean-Jacques Salomon.  Salomon, together with Israeli biologist Alexander Keynan, the principle author and editor of the 1998 volume, were the main organizers of the project along with Jeffrey Salmon, former executive director of the Marshall Institute.

As an American, I find several aspects of the papers striking.  Looking back to World War II, I am impressed by the quick, clever, and numerous roles international scientific cooperation played in the normalization of relations after the War.  Actions were taken directly between the key bloodied dyads, such as England and Germany and France and Germany.  But third parties, such as the scientific community of Denmark, also played vital roles.

The successes in normalization rapidly evolved into activities to promote the next step, European integration.  This integration refers primarily to the early seven or so members of the European community.  While politicians created European Community institutions to deal with coal, steel, and other shared economic concerns, durable transnational scientific institutions also arose in fields such as nuclear research (CERN), space science and meteorology (ESRO/ESA), and molecular biology (EMBO).  Importantly, the scientific institutions often previewed the diplomatic issues for the economic institutions.  Which countries could belong under what terms?

One question now of course is how science contributes to a Europe not of seven nations but of forty or so.  Europe is both integrating and fragmenting.  What roles does scientific cooperation play in reducing conflict when not only are new states joining in the East but also Scotland, Wales, Brittany, the Basque regions, Corsica, Northern Italy, and other regions seek more autonomous voices?  Perhaps science’s power to contribute to the reduction of common problems of industrialized societies will help tip the scales toward peaceful relations.  The high cost of the ante to enter the game of modern science in some fields might also favor integration.  For common action, science’s networks must penetrate rather fully into all the duchies of the emerging neo-medieval Europe.

Europe is changing in another important way for scientific cooperation.  Christian Europe, the usually tolerant host of most science for the seven centuries since Roger Bacon, is fading.  Demographically, Europe is becoming Muslim and African.  Will the new Europeans, who could form the majority by 2050 or so, tolerate science and enter effectively into its networks?  And can science form bridges to the Mahgreb and other regions with which 21st century Europe might conflict?

By now it should be clear that the quartet of scientists, war, diplomacy, and Europe belong together on one stage.  In fact, George Marshall understood this.  His plan included not only economic but also agricultural and technical assistance.  For the rest of us, less experienced and wise than Marshall, I hope this and the earlier volume on scientists’ roles in mitigating conflict between belligerent or recently belligerent nations prove the capability, as well as limits, of scientists in conflict resolution.  And I hope that more scientists, diplomats, and others concerned with international relations will make use of the practical possibilities that definitely exist.

Table of Contents

Scientists, war, and diplomacy:
European perspectives

Jesse H. Ausubel, Alexander Keynan, and Jean-Jacques Salomon, editors

Technology in Society 23(3), 2001
Special Issue

1. Jesse H. Ausubel and Alexander Keynan
   Foreword: The history of studies of scientists’ roles in international conflict resolution
2. Jean-Jacques Salomon
   Scientists and international relations: a European  perspective
3. Arnold Burgen
   The United Kingdom and the reconstruction of German science: the rebirth of the Kaiser-Wilhelm-Gesellschaft
4. Joseph Rovan
   France-Germany 1945: building a common future
5. Alexander King
   Scientific concerns in a Post-War economic  environment: science in OEEC-OECD
6. André Lebeau
   Scientific organizations and European unification: a personal view
7. William A. Nierenberg
   NATO science programs: origins and influence
8. Fernando Carvalho-Rodrigues
   NATO science programs: putting scientists and politicians in the same loop
9. Regina Gusmão
   Research networks as a means of European integration
10. Rudolf Botzian
    Scientific cooperation and technical assistance in German foreign policy
11. Hartmut  Kaelble
    Science and Franco-German reconciliation since 1945
12. Pierre Grémion
    The role of the social sciences in East-West relations
13. Geneviève Schméder
    A reconsideration of the idealistic vision of science for peace
14. Pieter J. D. Drenth
    Scientific academies in international conflict  resolution
15. Eugene B. Skolnikoff
    The political role of scientific cooperation
16. Abdelhamid Chorfa
    Maghrebi scientists and regional conflict
17. Nur Yalman
    Science and scientists in international conflict:  traditions and prospects

Foreword:
The history of studies of scientists’ roles in international conflict resolution

Jesse H. Ausubel and Alexander Keynan

Jesse H. Ausubel directs the Program for the Human Environment at The Rockefeller University in New York City.  From 1979 to 1981 he researched global warming at the International Institute for Applied Systems Analysis, near Vienna, Austria, a think- tank established by the Soviet and U.S. academies of sciences to study common problems of industrialized societies.

Alexander Keynan, a microbiologist at the Hebrew University for much of his career, is now based at the Israel Academy of Sciences & Humanities.  Dr. Keynan co-chaired the Committee for Scientific Cooperation between Israel and Egypt from 1979 to 1984.

Observers of the scientific enterprise broadly accept that science is international in scope and activity, and that international cooperation has always been intrinsic to it.  Indeed, much experience suggests that the permanent framework of international intellectual communication that operates among scientists is essential for the advancement of science.

After the bombs of World War II, scientists became increasingly aware of their social responsibilities.  Some scientists used their communication networks not only for cooperation in science, but also to reach across international lines of conflict, in attempts to mitigate such conflicts.  Some of these activities are well known and documented — for instance, the activities of the international Pugwash movement, which was recognized with a Nobel Peace Prize in 1995.  Many other activities of similar nature but smaller in scope, or limited to regional conflict, are little known and less documented.   Until recently, scholars had not examined these activities and their influence on international relations.  Several of us with personal experience in these activities became aware of their increasing scope and concluded that they merited serious study.

In the summer of 1995, Alexander Keynan, after consultation with Jesse Ausubel, Joshua Lederberg (President Emeritus of The Rockefeller University), and Rodney Nichols (President of the New York Academy of Sciences), submitted a proposal to David Hamburg (then President of Carnegie Corporation of New York) to launch studies on “Scientific Cooperation and Conflict Resolution.”  Hamburg at that time co-chaired the Carnegie Commission on Prevention of Deadly Conflict.  The Commission was keen to explore the roles of several occupations, including journalists and spiritual leaders, in conflict prevention, and science was obviously an interesting occupation in this regard.  In 1996 Carnegie Corporation supported a 3-year project, to be conducted under the auspices of the New York Academy of Sciences.  Because little documentation existed on the subject, the project began with a series of case studies on particular conflicts (such as US-USSR and Israel-Egypt), institutions (such as Pugwash), and natural science disciplines (such as seismology).  Most of the studies were conducted by scientists who themselves participated in attempts to use scientific cooperation for international conflict mitigation and drew on many interviews with other scientists involved in these activities.

An international conference January 28-30, 1998, at the New York Academy of Sciences on “Scientific Cooperation, State Conflict – the Role of Scientists in Mitigating International Discord” discussed the case studies as well as a preliminary synthesis of the literature.  The New York Academy of Sciences published selected papers from the conference as volume 866 of its Annals in late 1998, edited by Allison L.C. de Cerren[tilde]o and Alexander Keynan.  The volume contains 10 examinations of scientists’ efforts to mitigate international conflicts as well as a long introductory essay summarizing relevant literature, the case studies, and the discussions at the meeting.  At publication this volume was the most complete (and probably the only) study on this subject based on much empirical data.

Although the NYAS project included a case study of the Argentina-Brazil conflict, it emphasized U.S. experience during the Cold War and the Middle Eastern conflict.  Attendees at the New York conference pointed to the wealth of experience of cooperation among European scientists after World War II within Europe, cooperation that was not documented or debated.  Moreover, the scope of the NYAS project did not include studies of cooperation in the social sciences nor make much use of the analytic frameworks of the social sciences for examining the experiences in question.

Mindful of these omissions, the French historian of science Jean-Jacques Salomon offered to convene an additional conference based on European experience, broadening the scope of scholarly networks considered to include such disciplines as economics, and deepening the perspectives offered by political economy and other fields.  The meeting, entitled “The Impact of Scientific Cooperation Between Nations – Preventing and Solving Conflicts,” was held February 24-26, 2000, organized by the George C. Marshall Institute (Washington, D.C.) and Futuribles International, which generously hosted the meeting at its Paris offices and did most of the important practical work for it.  The sponsors of the meeting were the Richard Lounsbery Foundation (Frederick Seitz, President), NATO’s Scientific and Environmental Affairs Division (Fernando Carvalho-Rodrigues, chief), American Standard Companies, Ministère francais des Affaires Étrangères (Yves Saint-Geours), Fondation Léopold Mayer (Richard Petris), and Fondation La Ferthé (Gérard Toulouse).The organizing committee included some participants in the New York Meeting (Jesse Ausubel, Alexander Keynan, Klaus Gottstein, and J.-J. Salomon) as well as Hugues de Jouvenel (director of Futuribles), Andre Lebeau (author in this volume), and Jeffrey Salmon (director of the Marshall Institute).  Annie Palmentier ably assisted with all arrangements and Ann Johnston and Dale Langford with translation and editing.  For the high intellectual level and success of the conference, special acknowledgment goes to Jean-Jacques Salomon, who proposed its general concept, led in the selection of participants, introduced the issues, and now interprets the results.

As is clear in selected papers prepared for the conference and published in this volume of Technology in Society, the Paris conference differed greatly from the one in New York, but they share the strong sense that both an intellectual and a practical opportunity reside in this field.   Many relevant conflicts, institutions, and intellectual networks remain unexplored by scholars.  And many diplomats and others concerned with international relations remain unaware of the potential within the scientific community for action for conflict mitigation.  We are grateful to George Schillinger and George Bugliarello for this chance to make information and insights in this field more permanent and accessible.  We hope that the discourse begun in New York and Paris will continue and deepen understanding and use of the relationships between the international networks of science and all societies.

[1] J. H. Ausubel, A. Keynan, J.-J. Salomon, eds., Scientists, War, and Diplomacy: European Perspectives, Technology in Society 23(3), 2001.

[2]A.L.C. de Cerreno and A. Keynan, eds., Scientific Cooperation, State Conflict: The Role of Scientists in Mitigating International Discord, Annals of the New York Academy of Sciences 866, 1998.

[3] B. de Jouvenel, On power: The Natural History of Its Growth, translation by J.F. Huntington, Liberty Press, Indianapolis, 1993.

See the game that resulted from this research – Virtual-U

Colleges and universities are complex and arcane enterprises. They create and archive fundamental and pragmatic knowledge. They educate our young in preparation for adult life and society’s various endeavors. They interpret and critique culture and influence our world views. We expect these institutions to be all things to all people: generator of inventions for industry, spur for regional economic development, surrogate home for the young, guarantor of good jobs and high incomes, professional developer of those in mid-career, entertainer on Saturday afternoons, equalizer of social opportunity, and political refuge. As important as colleges and universities are to us, however, they are not well understood at a systems level even by those who live and work inside them.

This lack of understanding mattered less when the academy was held in high esteem and resources flowed to it at rates sufficient to maintain internal stability. But times have changed. The gleam of the ivory tower has dulled. A growing number of critics now believe that while educational services are central to America’s successful future, existing colleges and universities are failing to adequately manage their affairs, adapt to changing student needs, and exploit technological possibilities. Internal strife, from heightened competition for scarce resources among a heterogeneous mix of campus constituencies, makes governance increasingly difficult. Tools that can provide leaders both inside and outside the academy with a greater shared insight and und erstanding of our institutions of higher learning as dynamic systems are needed. This paper proposes one such tool.

The Need

Overemphasizing higher education’s importance in America is hard. It is a huge and influential enterprise. Roughly half of all young people enter a higher education institution. About 15 million students currently enroll. Faculty number about 900,000. In 1995, spending totaled close to $180 billion.

As a result of mounting difficulties in raising revenues, rising expectations for the role of universities in social and economic development, technologies that extend the ways in which education can be delivered, and shifts in student demographics and graduate labor markets, many academic leaders are seeking to move beyond incremental change and embark on more fundamental restructuring. Debate has in fact spilled beyond the borders of academe into the contents of best-selling books, lawsuits, and other areas on such issues as:

• the fundamental roles of the university (mission, vision)
• the relative emphasis on research, quality of teaching
• the need, quality, and character of basic research
• the appropriateness of applied research on campus
• faculty responsibility and behavior
• (excessive) management and (lack of) leadership
• costs, especially tuition and overhead rates
• the rationale for and length of time to the doctoral degree
• employment terms for the academic workforce
• curriculum content and knowledge structure
• elitism, social stratification, and diversity
• academic standards (e.g., admission policies, attrition rates, grade inflation, sports)
• the rise of foreign student population and links to foreign firms

The desirable response from higher education seems clear enough. From community colleges to research universities, they should raise productivity, modernize administrative and support services, and improve accountability while preserving autonomy. Upon identifying priorities, they should recast incentives and allocate resources accordingly. But how to go about achieving this response is less clear. A major obstacle is that key stakeholders appear not to recognize or accept facts about how colleges and universities work. They do not view the institution as a system or internalize the linkages between cause and effect. The resulting gaps in knowledge and credibility form major barriers to experimentation and reform. For example, seemingly logical proposals to close marginal departments and redeploy their faculty are vigorously fought. Conversely, incentive programs for early retirement are readily accepted even though they may generate unintended and undesired consequences (e.g., those who leave may be among the institution’s more productive faculty since they are more likely to have compelling career alternatives).

A large share of the problem owes to the fact that universities are complex, both to understand and to manage. Considering their functions and interactions with government, industry, and society in general, we can hardly be surprised. Universities are systems with many independent parts and interactive processes. Outcomes frequently depend on powerful but obscure second-order effects. One example is how the expansion of graduate education created a market for low-cost provision of labor for research and teaching, which now strongly influences the size of graduate programs and admissions, including the admissions of foreign students.

Some of the complexity in managing the system stems from lack of agreement or clarity among the various stakeholders about purposes, measures of performance, and productivity. Furthermore, the professional workforce and relatively flat organizational structure limit the exercise of direct management control, leaving institutional leaders to reconcile conflicting objectives as each stakeholder presses his or her own agenda. Stakeholders often attend only to their own values and needs, not stopping to see their institution in broad perspective. The decision-making process becomes volatile when emotionally charged issues such as tenure, academic freedom, and diversity are perceived to be at stake. Choices ultimately made may not be congruent with the institution’s long-run interest.

Most academic leaders come to their jobs lacking deep experience about economic and management matters. Intelligence and motivation can offset their inexperience to some extent, but organizational complexity limits the offset. The difficulty of achieving a comprehensive view also applies to trustees, faculty, staff, students, and others involved in university decision-making. Trustees are typically grounded in a business or professional field but often lack recent first-hand exposure to the higher education environment. Faculty rarely view their institution holistically, and the same is true for students, alumni, and other stakeholders.

Higher education needs innovative devices that help institutional leaders focus their thoughts, and then communicate with stakeholders without appearing manipulative or quickly raising defense mechanisms. Traditional devices such as conferences, commissions, and editorials help, but people rarely internalize complex scenarios by passively receiving information. A program to understand the college/university as a (complex) system, synthesized in a leadership strategy simulation game, can provide people at several levels with an opportunity to deepen their understanding of how colleges and universities work, motivating and engaging them without imposing the difficulties and risks that come with real life.

People concerned with higher education need to understand the decision-making process of the major actors–administration, faculty, students, and other internal and external stakeholders–and how these processes interact. Modeling the behavior of various subsystems within the university, their interactions, and the influence of external forces upon them can contribute to such an understanding. The parts of the system to be analyzed and modeled in detail will depend on what are considered the most important issues. Since controllability of the entire system is of paramount concern, priority would attach to building a model of the behavior of the entire complex system–yielding an intriguing, though necessarily rough, view of the whole.

A Leadership Strategy Game: “SimU”

The development of a college/university simulator, or “SimU,” would draw on three streams of activity: (a) management education games now widely used in management education (e.g., MIT and Carnegie Mellon distribute corporate management games popular in business schools); (b) special-purpose simulations developed to meet educational objectives in enterprises of various kinds (e.g., military battlefield simulations, nuclear power plant operations simulations); and (c) more purposely entertaining simulation games developed for a broader commercial market. Games such as SimEarth and SimCity (both developed by Maxis Software, the latter with sales of 2.5 million units) have proved to enlighten as well as amuse. Although formal evaluation of their effectiveness is hard to obtain, their enthusiastic adoption in school and university courses suggests their educational value. More explicitly serious simulations in this genre such as SimHealth (developed by Thinking Tools, Inc., to explore the reorganization of the US health care system implied by the Clinton health care reform proposals) have also had reasonable commercial success (sales of tens of thousands of units).

The games use continuous computation and constantly changing color graphics as well as sound to sustain user interest. Individual players “play against the model.” SimCity, for example, confronts a single player with zoning, infrastructure, transport, security, and fiscal issues played out over a sweep of time sufficient for long-term effects to become apparent. Efforts at developing multiuser online simulation games (e.g., the Internet-based “President ‘96” and “Reinventing America,” developed by Crossover Technologies under grants from the Markle Foundation to simulate the political and policymaking processes) are also now attracting considerable interest.

The authors believe that existing research and data are sufficient to build a simulation, both educational and entertaining, that will allow users to grapple with issues such as:

1. strategic positioning of the institution
2. academic performance and faculty morale
3. administrative and support service performance and staff morale
4. incentives and rewards
5. goals and perceptions of students, parents, donors, research sponsors, community members, employers, and government
6. comparative performance with respect to similar institutions
7. tuition, financial aid, and overhead rates
8. financial performance, including capital assets and liabilities (e.g., endowment, physical assets, and deferred liabilities)

The target market for such a simulation would be, broadly, anyone with an interest in how colleges and universities work as systems and, more specifically:

• higher education administrators
• faculty, especially those in leadership roles (e.g., department chairs)
• trustees
• education analysts, writers, and policymakers
• students of higher education, and in general
• alumni and interested public

How SimU Might Work

One of the biggest challenges in building the simulation will be to develop a successful user interface. It should be highly graphical and easy to understand and use. It should draw users to a depth sufficient for meaningful learning while at the same time maintaining interest, pace, and playability. Users report playing SimCity many times to experience its wide variety of different scenarios, exogenous events, and patterns of consequences. SimU should elicit a similar degree of interest.

SimU might open by inviting the user (you) to choose among institutional types and control. Do you want to lead a private research university, a public comprehensive, a private liberal arts college? In what year would you like to begin play? What would you like to name it? You might choose to “grow your own” generic institution or load one of a handful of pre-scripted scenarios that present a specific institution in the throes of a specific dilemma based on actual case studies. The scenarios would define “victory goals” that you must achieve to “win.” (In regular game mode, you will be free to define what success means yourself as you hone your own goals over time. ) Versions of the game might be developed that would allow tailoring to match more closely your specific real-life institution (e.g., through the loading of custom data sets).

Play might open with a panoramic view of the campus: a map with icons representing various organizational units and functions that then segues to a close-up of “Old Main,” your administrative headquarters. Double-clicking on it reveals the interior of an office (yours) complete with desk, file drawers, computer (for e-mail and information display), perhaps a door to a conference room in which meetings could be conducted and a window overlooking the campus that reveals significant changes in various aspects of the campus environment (e.g., dilapidated buildings if maintenance is deferred for too long, fewer students milling around if enrollment declines substantially, hostile faculty if you have not recently appeased them). You, by the way, are the president/senior administrator of this institution and have been blessed (burdened?) with an uncannily high degree of omnipotence.

Clickable icons to the side of the screen could represent schools and departments, offices for managing various functions (e.g., admissions, fund raising, buildings and grounds department), athletic facilities, dormitories, etc. Clicking on an icon would provide information about and/or encounters with the people or activity–analogous to searching out reports and management by walking around. Figure 1 provides a sampling of the kinds of activities and reports that might be included in the simulation.

Figure 1. Sample Activities, Decisions, and Reports Operating Units Academic departments Student services and student life Admissions and financial aid Institutional advancement Alumni relations and public affairs Libraries Information technology support Intercollegiate athletics Finance and administration Plant operations and maintenance Dormitories and food service Financial Decisions & Reports Operating and capital budgets Tuition rate and financial aid policy Research overhead rate Sources and uses of operating funds Faculty and staff salaries Faculty early retirement buyouts Endowment asset allocation and investment return Debt issuance and retirement Balance sheet operating surplus/deficit Other Actions & Reports Admissions selectivity and yield Enrollment by degree level and major Attainment rates & times to degree Course offerings Teaching method mix Course availability Class size distributions Teaching loads Sponsored research volume Publications record Faculty awards, prizes, etc. Popular prestige ratings Academic prestige ratings Faculty age distributions Faculty hiring & retention Staff additions and layoffs Staff turnover rates

At this point you might proceed in one of two ways. You might provide a set of presidential goals: in effect, a “platform” that calls out the priority you attach to various stakeholders and outcomes. Or, you might begin by playing with the goals programmed into your chosen scenario. These goals would influence certain aspects of simulated behavior. Moreover, they would provide the institutional performance benchmarks needed to define what it means to “win” the game. Alternatively, you might choose to simply explore the simulated world. Rather than trying to “win,” you would be occupied with observing the intuitive and sometimes surprisingly counterintuitive consequences of various inputs you and others (driven by the underlying game engine) make over time.

Semester by semester, time passes as you observe (and seek to modify) outcomes like faculty gains and losses, shifts in applicant pool and graduation rates, growth or decline in externally sponsored research, crumbling buildings and infrastructure, and accreting or eroding financial health. Conditions permitting, you might raise or borrow money and construct new facilities. You may at any time review data in your office or by walking around, call meetings, or change certain policies. (Nothing will happen at the interface while you are engaged in one of these activities, but computations will continue in the background.)

You might visit a particular department and perhaps try to influence faculty behavior: e.g., numbers and types of courses, teaching loads, submission of proposals for sponsored research, involvement with students outside of class. Such efforts might or might not be successful, depending on the institution’s incentive-reward environment (which would stem in part from your own prior decisions) and other circumstances. Even if successful, they might exact a price in faculty morale–however, the opportunity to exert influence would allow you to seek changes at the academic working level that might otherwise appear out of reach.

Three kinds of pre-programmed events punctuate the passage of time:

• Scheduled events marking milestones or providing periodic information for which no response is required: e.g., quarterly and fiscal-year financial reports, key athletic outcomes, admission of the next freshman class, commencement. Simulated time continues.
• Scheduled events for which a response is required: e.g., submission of the annual tuition recommendation, the operating budget, and the capital budget; and the Board’s annual presidential performance evaluation and your acceptance or disagreement with it. Simulated time halts while you prepare the budget or react to the performance evaluation.
• Unscheduled events arising exogenously or because of some condition within the simulation: e.g., a stock-market crash, a dean or professor pleads a case or airs a grievance, a Faculty Senate action or student protest, a fire or a safety problem. Simulated time may continue or halt depending on the event.

By combining these events with the user-initiated ones, the SimU program should be able to provide a simulation that is sufficiently rich to realistically represent the essentials of university leadership and capture user interest. Most of the databases needed to specify the model already exist, and a growing number of research findings are available. Indeed, pulling together the information needed to build the model will be a valuable exercise in its own right. A companion handbook and strategy guidecould provide background, help focus play, and draw out lessons contained in the simulation.

SimU Actors

We have already described how you (as institutional leader) might interact with the SimU simulation. But in a university, the administration’s word is not exactly law. Much of what happens in SimU would result from the actions of various constituencies–simulated actors and stakeholders that operate inside or outside the university. Your actions would influence constituency behavior, but not control it.

A list of potential constituencies follows. Some are depicted as individuals while others represent aggregations of individuals. Some would appear in the simulations for all institutional types, others would apply to one or two types only. At this point we do not know how practical it will be to include all the following constituencies in the game’s initial version.

Internal constituencies

• The governing board might provide financial oversight and offer evaluations of presidential performance .
• School deans might be simulated as independent agents who have independent objectives and sets policy.
• Faculty in each department might be simulated as a set of cohorts with age-rank characteristics and probabilities for promotion, departure, and retirement.
• Department chairs might decide about course offerings, teaching loads, and research emphasis–in effect, representing the aggregate view of departmental faculty.
• The faculty senate might represent the view of the faculty taken as a whole.
• Students might be simulated in terms of admission cohorts, degree levels, and majors, each with course-taking, graduation rate, satisfaction, and similar characteristics.
• The student senate might represent aggregate student views.
• Non-academic operating units–e.g., support services, administration, operations and maintenance–might be described by production functions relating the quality and quality of outputs to budget allocations (see the list in Figure 1 for a more complete list).
• The non-faculty workforce (staff) might be portrayed as a small number of groups–e.g., professional and administrative, clerical, operations and maintenance–whose numbers would grow or ebb according to budget allocations; staff morale and efficiency might depend on workload in relation to numbers, and on compensation level.
• Prospective students might be simulated in terms of application and matriculation rates by market segment; “market research” data might be used to convey attitudes and predict behavior.
• Research sponsors might be simulated on a discipline-by-discipline basis, with each discipline characterized by the level of total funding and the intensity of competition.
• Alumni and potential donors might be simulated according to their interest in one or another department or in the whole institution; gift-giving might depend on department/institution performance and prestige.
• The media might be simulated as a single constituency, with media actions being illustrated with newspaper clippings or television stories.
• Public opinion also might be simulated as a single constituency; public opinion might drive regulatory decisions, and influence state funding decisions in game sessions dealing with public institutions.

Exogenous factors also might affect SimU’s fortunes. Economy-wide inflation and family income growth might drive up cost and mediate the effect of tuition increases on admissions yield and public opinion. Demographics might affect student demand. Governmental funding decisions might drive sponsored research, and for public institutions, state appropriations. A natural disaster might disrupt campus operations. Technological change might restructure cost functions and engender new competition that challenges market shares in education or research. Presidential actions throughout the simulation would determine how well the institution weathers the storms and captures and opportunities.

Issues to be Addressed

SimU would address at least four kinds of issues. The interaction of player decisions with data and response functions built into the model would determine how a college or university evolves and whether the president’s goals are achieved. Gaining insights about these issues and learning to analyze them in systems terms would constitute one of SimU’s most important benefits. The issues include:

1. Capital investment vs. spending for current operations (spending vs. saving): policies governing financial capital (endowment, reserves), physical capital (facilities, equipment), and spending for operations. Most institutions bias decisions toward spending for current purposes, especially salaries. The simulation would address the consequences of such imbalances.
2. Operating budget allocations: decisions to spend more on one field or activity than another; determination of cross-subsidies between fields and activities. Spending on certain fields may be seen as more or less consistent with the school’s mission, and fields will vary in their ability to generate enrollments and sponsored research dollars. Spending on academic support services may improve educational and research quality and competitiveness, institutional-support investments (e.g. G&A and O&M) may improve infrastructure and efficiency, institutional-advancement investments may increase giving levels, and so on.
3. Transactions with customers and stakeholders: student applications, admissions, and yields; sponsored research finding; gift acquisition; and, for public institutions, state appropriations. Outcomes may be affected by quality and prestige, net prices (e.g., tuition minus average financial aid, the effective research overhead rate), and “marketing” expenditures (e.g., for admissions and institutional advancement), as well as uncontrollable factors.
4. Academic department actions, which produce the institution’s instruction and research outputs. The range of simulated action might include: the profile of courses as represented by teaching method mix (lectures, seminars, labs), course level, and degree of specialization; faculty teaching loads; and the degree of emphasis placed on research. Considerable attention would be placed on departmental actions because such actions constitute the central focus of academic production.

Success Criteria and Performance Measures

Both game designers and players will have to address basic questions dealing with the university’s or college’s fundamental mission. Should the mission stress the preservation and transmission of knowledge (teaching) or the generation of knowledge (research)? Should the mission cater to the few or virtually everybody (the elite or the mainstream)? Should the institution focus its mission or should it try to serve a broad set of constituencies?

The SimU simulation would be rich enough to permit a large number of performance measures to be reported, but it would not dictate what players should pay attention to. Indeed, much of the data available as a byproduct of the behavioral simulations would not be displayed unless the player searches it out by clicking on the appropriate icons. While certain success criteria would be defined–either by the player or as part of the chosen scenario–the player will retain a great deal of latitude.

Much of SimU’s value will come from discussions about values, performance measures, and the functions programmed into the game. These discussions would be stimulated but not brought to closure by the software and supporting data. The players themselves would have to supply the missing pieces, but the game would supply two crucial elements.

1. First, the game would provide a specific set of stimuli for discussion–a context within which to explore one’s own values and understandings and, depending on the circumstances, to compare them to those of one’s colleagues.
2. Second, the game would enforce the disciplines of conservation and causality. Money allocated to one priority is not available for another. Actions and failures to act have consequences that must be considered when trying to satisfy one or another constituency. All constituencies cannot be satisfied to the full extent of their desires, especially when exogenous forces infringe on the institution’s market power or freedom of action.

These are important lessons in their own right, and their application in the context of discussions about values would add yet another important benefit. Without consideration of conservation and causality, discussions about values become unbounded, and the university is urged once again to be all things to all people.

Conclusion

The motivation for using SimU is to understand better how a university works. What performance measures should be considered? How do decisions made by the administration, the faculty, and other agents affect the performance measures? Why can’t the university simultaneously maximize the agendas of all its stakeholders? Some participants will challenge the theories used in the simulation, but the very act of challenging requires the formulation of an alternative hypothesis–which can be analyzed and compared with assumptions and data used in the model. SimU also should be fun to play, since learning depends on engagement and engagement will be stimulated and sustained if the activity is intrinsically interesting.

Faculty, staff, students, and trustees must develop more coherent and realistic perspectives about their institutions. Working with a simulation game can build experience and broaden perspectives. Gaming can help all stakeholders understand issues at the level of the institution–and from viewpoints of other stakeholders–and see the issues through less parochial eyes. Even experienced managers find that playing a sophisticated game expands their horizons and motivates broader discussion of management issues.

Ultimately, we would hope that development of SimU would bring three benefits:

1. New knowledge: advances in fundamental understanding of how a university functions will come from facing for the first time the challenge of modeling the whole of a university.
2. Education of a broad group of stakeholders: given a reasonably sound simulator, a rather large number of stakeholders, numbering in the tens of thousands, may enhance significantly their understanding of the university as a system by “playing the game.”
3. Development of new management tools for universities: while SimU would be generic, it could prove the concept of university simulators and stimulate the subsequent development of more detailed, realistic simulators appropriate for specific institutions or classes of institutions.

The authors understand the difficulty of considering the university as a complex system. But because complexity lies at the heart of the university’s current problems, we feel it is important to address the issue head-on. Even the limited models that are practical using today’s knowledge can begin to capture the dynamics and the interactions of the parts. At a minimum, they can help organize the data that will be needed to simulate a university in finer grain, and they will lead to better definition of parameters, variables, and outcomes. But the real payoff–achievable, we believe, with today’s technology–will be to move higher education’s many constituencies toward more shared understanding of how the academy works.

Notes

¹ This paper was motivated in part by a session on simulation an gaming, led by John Hiles of Thinking Tools, Inc., at last fall’s Stanford Forum for Higher Education Futures (Annapolis, November 1995).