Learning to do social science research in the knowledge economy: A manifestoMartin Terre Blanche
In this article I outline some of the key characteristics of the global knowledge economy and attempt to identify matching sets of skills that should be (but often are not) taught in social science research courses. I describe the knowledge economy as global, highly networked, subject to rapid turnover, as treating knowledge as a commodity, and as existing in a perpetual state of "scarcity in abundance". Each of these characteristics is suggestive of a particular body of knowledge and set of skills needed to operate in (and against) such an economy.
Every year hundreds of thousands of students worldwide do courses in social science research methods. They typically learn how to design complex experiments and surveys, run focus groups and conduct interviews - but not how to find a worthwhile research question or how to use their knowledge to make a difference in the world. They are warned against a million-and-one methodological pitfalls - but not encouraged to use their creativity and passion to construct useful new knowledge. They are drilled in the rigours of painstaking, bureaucratic research procedures - but not in how to make their way through a world of constant, rapid change.
In this article, written in the form of a manifesto, I suggest that social science researchers need different sets of skills from those currently being taught in research methods courses. I describe some of the key characteristics of the new knowledge economy - namely that it is global, highly networked, subject to rapid turnover, treats knowledge as a commodity, and exists in a perpetual state of "scarcity in abundance" - and outline the types of knowledge and skills needed to do research within (and in opposition to) such an environment. For each characteristic of the new knowledge economy I start with a short, programmatic statement about the characteristic and what it implies for social science researchers, and then provide a more detailed exposition.
Local events are conditioned by global knowledge systems. Therefore researchers need to develop a critical and historical understanding of global political and economic agendas, and of globally powerful ideologies.
Globalization is not something that suddenly arrived in the second half of the twentieth century, but is a process which has been unfolding at least since the 15th century with Columbus’ journeys of discovery (Bonanno, Busch, Friedland, Gouveia & Mingione, 2000). However, in the last several decades it appears to have speeded up to an unprecedented degree with societies everywhere increasingly exposed to international economic and political forces, and global culture (ranging from consumer fashions to the English language) increasingly seeming to displace a great diversity of indigenous knowledge systems (Ho, Novotny, Webber & Daniels, 2003). Much of what passes for research in the social sciences, especially in psychology, deliberately ignores this broader socio-historical context - attempting either to discover trans-historical facts about human nature (as in traditional experimental research) or to focus exclusively on unique, local phenomena (as in traditional phenomenological research).
To do research that has relevance to the intensely global nature of 21st century society, we need three kinds of knowledge.
First, we need to understand the explicit political and economic agendas pursued by various players on the global stage. What are the aims and strategies of the IMF, the World Bank and of economic and political superpowers such as the United States and Europe? What counter-strategies and alliances are in place? What are the historical circumstances that gave rise to the current state of affairs? While it may not be necessary for all social science researchers to become experts on globalization, there is now a large semi-popular literature (cf. Friedman, 2000; Klein, 2000) on the topic which makes it relatively easy to develop at least a basic understanding of the main issues.
Second, we need to have some understanding of the unstated but pervasive ideological assumptions now governing large and small social interactions across the world. To live as a middle class person in the modern world is more often than not to take certain things for granted - that meaning is created by and basic rights are vested in the individual rather than the collective; that reliable knowledge comes from careful, rational enquiry; that government is best conducted through a system of elected representatives; that scientific and technological progress is necessary and inevitable; that economic competition in a ‘free market’ is the best and most equitable way of creating wealth; that the ‘Third World’ is historically ‘backward’ and still needs to catch up to the more advanced nations; that black people need to become more like white people; that heterosexuality is normative; and that there is nothing remarkable about men occupying most positions of power. The point is not that pervasive ideologies such as these are morally or factually wrong (although many of them no doubt are), but rather that they form the ground against which the particular events social science researchers claim to study are enacted. Without some understanding of the critical theoretical literature in fields such as gender studies (e.g. Bozzoli, 1983; Daymond, 1996) and post-colonial studies (e.g. Fanon, 1967; Said, 1978), how can we hope to begin to do research that reflects the realities of the global world we are living in?
Third, we need to develop skills in using research approaches that consciously focus on social events as simultaneously local and global, unique and stereotypical in nature. Examples include feminist and other standpoint methodologies (Harding, 1987) which work towards an understanding of particular situations by starting from the general perspective of groups that have historically been the victims of oppression; critical discourse analysis (Parker, 2002) which seeks to trace how global discourses both set up the conditions for and are then rhetorically employed in local interactions; and critical participatory action research (Whyte, 1991) which positions research as a form of both local and global political activism.
Institutions no longer exist as clearly bounded entities, but are immersed in overlapping webs of cooperation and competition, and knowledge workers are no longer bound to single institutions. Therefore researchers need to develop an understanding of networks and learn how to become multiply and creatively linked into the knowledge web.
The twentieth century was an era of monopoly capitalism, and across the world the economic landscape is still dominated by giant corporations seeking to either incorporate or obliterate all competition. Yet at the same time it is clear that in the 21st century a different ethos and a different set of practices are on the rise. Even old-style juggernaut corporations such as Microsoft no longer simply have their value safely locked up in the form of exclusive financial and intellectual capital, but thrive by virtue of an increasingly complex network of alliances, partnerships and outsourcing arrangements in terms of which they freely share some of their key technologies in order to create the conditions for earning revenue from others (Bressler & Grantham, 2000; Gates, 2000; Means & Schneider, 2000). In this type of environment the old, stable forms of relationship between employer and employee are being supplanted by ad-hoc arrangements where expertise is bought in as needed to meet the demands of short-term projects. As a consequence, knowledge workers now have less job security and fewer opportunities to improve their circumstances through collective bargaining, but are also more able to explore different types of work and collaborate with a wider circle of colleagues around the world. Increasing numbers of knowledge workers are no longer employed by single institutions, but operate as small scale entrepreneurs, "portfolio people" (Comfort, 1997), loosely coupled to similar small and large scale entrepreneurial enterprises.
In a networked world, researchers first need to understand something about networks. With the rise of the Internet, there has been a flowering of mathematical and sociological theorising on how networks work (cf. Bollobas, 1998; Borgatti & Everett, 1999; Buchanan, 2002; Cross, Borgatti & Parker, 2002), and it is becoming essential to know something about concepts - such as "power laws","six degrees of separation", and "network spanners" - that flow from this work. Equally important is a feel for pragmatic networking realities such as how, for example, knowledge projects rise to prominence or sink into obscurity depending on how well they are linked into overlapping grids of related projects.
Second, researchers need to learn how to rapidly ‘map’ knowledge landscapes - visualising the relationships among key actors and institutions, recognising emerging trends, flagging major alliances and antagonisms. What is needed is more than the traditional literature survey in which the development of ideas is presented as if it occurred as a kind of rational, scholarly conversation conducted via academic journals. Rather the ways in which particular knowledge practices and understandings come into being and fade away need to be understood in terms of the business and politics of collaboration and contestation among different actors (individuals, commercial enterprises, NGOs, state institutions) and agendas operating in many different contexts in addition to academia.
Third, researchers need to learn the skill of forming and disbanding networks, of becoming part of existing networks, of gaining reputation within networks (Rheingold, 2002), of opening up opportunities for others to participate in networks, of helping to transform dysfunctional networks, of acting as a relay between different networks, and of disengaging from networks. In a networked world, the difference between creating knowledge and building community, if there ever was one, has dissolved. To do meaningful and effective research is now one and the same thing as critical but respectful engagement with communities of practice.
Knowledge as commodity
Knowledge is mass-produced, packaged, distributed, exchanged and sold as discrete objects. Therefore researchers need to learn to critically consume knowledge products; and to design and distribute knowledge products as re-usable objects with the aid of object-oriented design and standard knowledge distribution protocols.
More than two decades ago Lyotard (1979), in his now classic "report on knowledge", already observed that: "The relationships of the suppliers and users of knowledge to the knowledge they supply and use is now tending, and will increasingly tend, to assume the form already taken by the relationship of commodity producers and consumers to the commodities they produce and consume... Knowledge is and will be produced in order to be sold" (p. 2). The world Lyotard was beginning to see taking shape in the late 1970s is now with us. Like it or not, we now live in an era where data, information, knowledge (and possibly even wisdom) have become commodified, i.e. packaged and sold (or traded, or given away) as discrete, easily-manipulated units - like rows of canned goods on a supermarket shelf.
To operate in a world of commodified knowledge social science researchers need three types of skills.
First, we need to become adept at using packaged knowledge goods. This entails knowing when and how to simply make use of the knowledge being purveyed, just as we already routinely consume convenience foods or instantly "plug-and-play" electronic equipment, and when and how to critically engage with the implicit message communicated by the packaging in which the knowledge arrives, just as we already routinely do with other types of consumer product such as mobile phones or toothpaste tubes (Bannister, 1994). There was a time when academically useful knowledge would always be packaged in one of a very small range of carefully graded packages (books, peer reviewed journal articles, and so forth) and when it was necessary to painstakingly work through the content of each package to extract value from it. Increasingly, however, the boundaries between academic and popular products are becoming blurred and it is now often no longer necessary to actually open the package - simply reading the label (e.g. the title or the abstract) is enough to see how it can be used.
Second, we need to learn how to package our own knowledge products in ways that are easily consumable and that allow for their re-use in plug-and-play knowledge environments. In the world of computer programming it has become standard practice to design systems in a modular, object-oriented manner so that programming code can be more easily maintained and re-used (Booch, 1993). In this approach, programs are not designed as single large systems, but are broken into many independent objects, each of which appears as a simple, replaceable building block to the system, however complex the object’s inner workings may be. In the same way, in the world of information and knowledge management, it has become increasingly common to "hide" each complex knowledge object behind a set of meta data (analogous to the label on a soup can), so that it can be easily slotted in or out as needed, without compromising the stability of the larger system. (For example, the section on "knowledge as commodity" which you are currently reading has been written to function as an independent module so that it could stand on its own or be part of some larger product such as a journal article which might also contain other similar modules.) To build knowledge objects of this sort, researchers need to learn to think and work in terms of object-oriented design. What are the main classes of objects making up a knowledge product one is constructing? How can one ensure that each object is maximally modular so that it can be easily replaced? Which objects could be more efficiently produced by outsourcing them to someone else?
Third, we need to become proficient at using the many standard knowledge packaging standards and protocols already in use in the knowledge economy. These range from simple conventions which make it easier for humans to select and consume knowledge products (titles, subtitles, executive summaries, highlighting of key points) to the many technical protocols (such as HTML, XML and RSS) that allow for the efficient exchange of information among computer systems and programs. While few social science researchers will want to know about the technical specifics of such protocols, understanding their purpose and being able to use them greatly enhances one’s ability to engage with knowledge networks. RSS (Really Simple Syndication), for example, is a widely used convention that makes it easy to automatically include appropriate aspects of others’ work in one’s own knowledge products, and, conversely, to make one’s own knowledge products freely available in such a way that others can easily, and automatically, include it in their work.
The value of knowledge decays rapidly in a constantly changing global environment. Therefore researchers need to learn how to remain up to date with current developments, to create and deploy knowledge quickly, to manage time effectively, and to practice the art of just-in-time learning.
More than anything else, the modern era has been characterized by constantly accelerating change - technological change, political change, social change - and there is no sign that things are about to slow down. Even though we are, as Toffler (1970) observed, literally sick of change, we are also addicted to it. In the new knowledge economy things (have to) happen quickly. Fresh perspectives, technological innovations, new products and services, are what drives the economy, and organisations and individuals who are unable to keep up, who lack the necessary ‘agility’ (McCarthy, Stein, & Brownstein, 2002), are the ones who lose out.
To function effectively as social science researchers in such an environment, we need four types of knowledge and skills.
First, we need to keep up to date with new developments - tracking both broad political and technological trends and specific developments in particular fields of interest. This requires maintaining a constant watch on a variety of ‘popular’ and scholarly news sources - including academic journals, newsletters, weblogs and syndicated news feeds - and participating in networking events, such as conferences where information about the latest advances (and the latest gossip) is exchanged.
Second, we need to learn how to rapidly develop and deploy knowledge products before the window of opportunity within which they can be effective closes. While there will probably always be a market for painstaking empirical and theoretical work that unfolds over periods of many months and years, most often the type of knowledge that matters is that which can be brought to bear quickly. For example, when Unisa management recently approached the Centre for Social and Health Sciences to do an analysis of the dangers faced by students crossing a busy road near the university, the Centre could have turned the request into a drawn-out research project. Instead, they delivered a report detailing traffic statistics, opinions of various stakeholders, illustrative photographs, and cost-benefit analyses of various proposed solutions within a week. A year later, and a pedestrian bridge has been built and the risk to students substantially reduced. A very different example: The Slovenian philosopher Slavoj Zizek has in the last decade become one of the most influential and sought after cultural analysts in academia. In part he has achieved this status as a result of his closely argued and startlingly original academic writings (e.g. Zizek, 1992; 2001), but in part it also results from the constant stream of almost instantaneous commentaries he provides (via magazines, newsletters, conference presentations, radio interviews and the like) on unfolding world events. To create and deploy knowledge quickly we need to learn the skills of rapid knowledge assembly, such as using ready-made components as building blocks for larger products, collaborating with others to make projects more manageable, and making use of techniques such as rapid prototyping (Jones, Li & Merrill, 1992) to speed development. We also need to learn to resist the temptation of ‘over engineering’ our products and to recognise when good enough is indeed good enough.
Third, we have to become more skilled and strategic in managing time as the most valuable resource available to us. For some, this might mean careful project planning to ensure that deadlines will be met. For others, it might simply mean finding a suitable rhythm of, for example, focussed work interspersed with periods of rest and reflection.
Fourth, social science researchers need to learn the skill of just-in-time learning. In a fluid, constantly changing environment it is the norm not to have the right knowledge and skills in one’s repertoire. What is needed then is the ability to recognise the gaps in what one knows and to become committed to being a ‘lifelong learner’ (Edwards & Nicoll, 2001).
Scarcity in abundance
Information is freely and abundantly available. Therefore researchers need to learn to disembed useful information, transform it into knowledge, and pass it along appropriately.
There was a time when there was a shortage of goods and services in the global economy, but this is no longer the case - enough food is cultivated every year and enough manufacturing capacity exists to feed and provide basic comforts for each of the 6 or so billion people on the planet (Lappé, Collins & Rosset, 1998). The fact that millions of people still go hungry is due to a failure of political imagination and will, not to any intrinsic scarcity. At the level of information, we now even more clearly live in an era of ‘post-scarcity’ (Ashford & Shakespeare, 1999) economics. Information is available in ever-increasing abundance and at ever-decreasing cost. Even though countries and regions within countries still share very unequally in the spoils of the information era, with some claiming that the world is split in two by a ‘digital divide’ between rich and poor, information technologies are spreading through the ‘developing’ world at an even faster rate than in the ‘developed’ world (Shirky, 2002). This over-abundance of freely available information has however, resulted in a new type of scarcity - that of information overload. We are now constantly confronted with simultaneously knowing too much (being overwhelmed by all the bits being piped into our consciousness) and too little (not being able to extract the important bits from the rest).
To thrive in such an environment, we need to learn two types of skills.
First, we need to learn how to filter out useless information. Whereas in a previous era the challenge may have been to track down and secure information as a scarce commodity, now we have to filter out noise in an effort to detect some kind of signal in the stream of junk data being beamed our way. At the simplest level this means learning how not to pay attention, how to look the other way, and how to make liberal use of e-mail programs’ delete buttons. More profoundly, it involves learning how to make use of filters to prevent unwanted information from ever reaching us. Probably the most effective filters are other humans whom we can rely on to screen and organise information on our behalf (as is done, for example, by Stephen Downes, 2003, for the online learning community). Such human filters take the form of favourite columnists, bloggers, academic authors, and so on whose take on events resonate with our own. However, in building a defensive wall of human filters between ourselves and the threat of information overload, it is important that we do not completely screen out all possibility of being surprised, or of learning fundamentally new things. If our human filters are all too much like ourselves in background, if they are all saying the same sorts of things, then it may be time to risk indulging in a little overload. In addition to human filters, we also need to learn how to use the increasingly large and effective array of automated filtering tools. Search engines such as Google now make it possible, as a matter of routine, to winnow out billions of pages of irrelevant information in an instant and to home in on the one or two pages that matter. Similarly, by carefully slicing, dicing and auto-filtering syndicated news feeds (Paquet, 2003) it is now possible to set up highly focussed streams of incoming news tailored to one’s particular requirements.
Second, we ourselves need to learn how to act as filters for others. Whether it is in the context of a money-making business or simply "for the good of the cause", central to what knowledge workers do is to collect and filter information and pass it on to others as knowledge. Often, simply sorting bits of disconnected information into commonly accepted (or novel) classification schemes already adds sufficient value to count as a desirable knowledge product. In other cases, we need to process the information in more profound ways to make it into something that others will want to use in their own knowledge projects.
I am conscious that this manifesto is a rather unusual mixture of different types of political and academic impulses. It seemingly celebrates free market entrepreneuralism, but also emphasizes theoretical understandings that are fundamentally critical of the market, and in fact advocates for a kind of communalism. It shamelessly revels in quick-and-dirty, make-do solutions, but also seems to want to hold on to some notion of reliable knowledge. In part, this is simply a reflection of my personal experience of the information era as simultaneously exhilarating and frightening. In part it may be, I hope, because these apparent contradictions are not in fact that contradictory after all, but are elements of what will hopefully develop into a more coherent understanding of what doing social science research in the information era might properly entail.
Ashford, R., & Shakespeare, R. (1999). Binary Economics: The New Paradigm. Lanham: University Press of America.
Bannister, P. (1994). Discourse Analysis. In Bannister, P., Burman, E., Parker, I., Taylor, M. & Tindall, C. (Eds.), Qualitative Methods in Psychology:A Research Guide. London: Open University.
Bollobas, B. (1998). Modern Graph Theory. New York: Springer-Verlag.
Bonanno, A., Busch, L., Friedland, W.H., Gouveia, L., & Mingione, E. (Eds.) (2000). From Columbus to ConAgra: The Globalization of Agriculture and Food. Lawrence: University Press of Kansas.
Booch, G. (1993). Object-Oriented Analysis and Design with Applications (2nd Edition). Addison-Wesley.
Borgatti, S., & Everett, M. (1999). Models of core/periphery structures. Social Networks, 21, 375-395.
Bozzoli, Belinda (1983). Marxism, Feminism and South African Studies. Journal of Southern African Studies, 9(2), 139.
Bressler, S., & Grantham, C. (2000). Communities of Commerce. London: McGraw Hill.
Buchanan, M. (2002). Nexus: Small Worlds and the Groundbreaking Science of Networks. New York: W.W. Norton & Company.
Comfort, M. (1997). Portfolio people. London: Random House.
Cross, R., Borgatti, S., & Parker, A. (2002). Making invisible work visible: Using social network analysis to support human networks. California Management Review, 44(2), 25-46.
Daymond, M.J. (Ed.) (1996). South African Feminisms. Writing, Theory, and Criticism 1990-1994. New York: Garland Publishing.
Downes, S. (2003). Knowledge ~ Learning ~ Community. http://www.downes.ca Downloaded 10 March 2004
Edwards, R., & Nicoll, K. (2001). Researching the rhetoric of lifelong learning. Journal of Education Policy, 16(2), 13-24.
Fanon, F. (1967). Black skin, white masks. New York: Grove Press.
Friedman, T.L. (2000). The Lexus and the Olive Tree: Understanding Globalization. New York: Anchor.
Gates, B. (2000). Business @ the Speed of Thought. Los Angeles: Warner Books.
Harding, S. (1987). Is there a Feminist Method? In Harding, S. (Ed.). Feminism and Methodology, pp. 1-14. Bloomington: Indiana University Press.
Ho, M., Novotny, E., Webber, P., & Daniels, E. E. (2003). Towards a Convention on Knowledge. Synthesis/Regeneration, 31, 1.
Jones, M. K., Li, Z., & Merrill, M. D. (1992). Rapid prototyping in automated instructional design. Educational Technology Research and Development, 40(4), 95-100.
Klein, N. (2000). No logo. London: Harper-Collins.
Lappé, F.M., Collins, J. & Rosset, P. (1998). World Hunger: 12 Myths. 2nd Edition. Grove/Atlantic & Food First Books.
Lyotard, J. (1979). La Condition postmoderne: rapport sur le savoir. Paris: Minuit.
McCarthy, M.P., Stein, J., & Brownstein, R. (2002). Agile Business for Fragile Times : Strategies for Enhancing Competitive Resiliency and Stakeholder Trust. McGraw-Hill.
Means, G., & Schneider, D. (2000). MetaCapitalism. The e-Business Revolution and the Design of 21st-Century Companies and Markets. New York: John Wiley & Sons.
Paquet, S. (2003). The algebra of feeds, or the amateurization of RSS bricolage. http://radio.weblogs.com/0110772/2003/09/11.html Downloaded 10 March 2004.
Parker, I. (2002). Critical Discursive Psychology. London: Palgrave.
Rheingold, H. (2002). Smart Mobs: The Next Social Revolution. Perseus Publishing.
Said, E. (1978). Orientalism. New York: Pantheon Books.
Shirky, C. (2002). Half the world. Downloaded from http://shirky.com/writings/half_the_world.html 10 March 2004
Toffler, A. (1970). Future shock. New York: Random House.
Whyte, W. F. (Ed.) (1991). Participatory Action Research. Newbury Park: Sage.
Zizek, S. (1992). Enjoy Your Symptom! Jacques Lacan In Hollywood And Out. London: Routledge.
Zizek, S. (2001). Did Somebody Say Totalitarianism? Five Essays in the (Mis)Use of a Notion. London: Verso.