Knowledge, Economy, Technology and Society: The Politics of Discourse
David RooneyUQ Business School and Centre for Social Research in Communication, University of
Queensland
11 Salisbury RdIpswich, Qld 4350
[email protected](07) 3381 1042
or(07) 3378 7534
Knowledge, Economy, Technology and Society: The Politics of Discourse
Abstract: The WSIS is centrally interested in knowledge and has defined for itself a mission that is broadly humanitarian. Its development ‘talk’ is, rightly, replete with notions of equity, preserving culture, justice, human rights and so on. In incorporating such issues into knowledge society and economy discussions, WSIS has adopted a different posture towards knowledge than is seen in dominant discourses. This study analyses the dominant knowledge-related policy discourse using a large corpus of knowledge-related policy documents, discourse theory and an inter-relational understanding of knowledge. I show that it is important to understand this dominant knowledge discourse because of its capacity to limit though and action in relation to its central topic, knowledge. The results of this study demonstrate that the dominant knowledge discourse is technocratic, frequently insensitive to the humane mission at the core of the WSIS, and is based on a partial understanding of what knowledge is and how knowledge systems work. Moreover, I show that knowledge is inherently political, that the dominant knowledge discourse is politically oriented towards the concerns of business and technology, but that an emancipatory politics of knowledge is possible.
Keywords: culture, technocratic discourse, information, knowledge society, knowledge economy, political economy
1.1 Introduction
Since the 1950s Development Communication has taken as it primary goal improving
the use of communication processes and the media to foster development within
emerging economies (see for example, Dissanyake 1986; Freire 1983; Lerner 1958;
Rogers 1976; Schiller 1969). In more recent years Development Communication and
The World Summit on the Information Society (WSIS) have become interested in the
role of information and knowledge in development. This new set of concerns means
that new research is needed in Development Communication and the WSIS to
promote an understanding of knowledge for researchers, policy professionals and
practitioners who serve the needs and concerns of developing nations (Rooney et al.
2003a). This article therefore outlines a sociological theory of knowledge (or
knowing) and discusses the discursive formations and politics of the dominant
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knowledge discourse to demonstrate troubling aspects of the construction of
knowledge policy globally.
This study analyses a large corpus of knowledge-related policy documents sourced
from a range of industrialised and industrialising countries, and demonstrates that the
global discourse on knowledge is technocratic (McKenna et al. 2000). I show that the
central concerns of the dominant knowledge discourse are about business and
technology rather than knowledge (and culture and society). This discourse is
significantly different to the central concerns and indeed the emancipatory agenda
(Habermas 1972) of WSIS participants and UNESCO more generally (see Rooney in
press). I seek to explore this technocratic discourse and lay bare its politics, values
and assumptions about knowledge and the development process.
2.1 KNOWLEDGE, DISCOURSE AND DISCURSIVE STRUCTURES
Knowledge is an elusive thing and the precise nature of it has been earnestly debated
for at least three millennia. Salient for Development Communication is that
knowledge has very clear links to development and language (Chomsky 1968;
Graham in press; Rooney et al. 2003a; Welbourne 2001). Foucault argues that the
‘approved’ knowledge of the day is a key means of exercising power to mobilise
various economic, social and cultural resources, and that this power becomes manifest
in the language of the dominant discourse (Foucault 1972; Foucault 1979). Thus, if
knowledge is related to power then ideas about knowledge, expressed in discourse,
must be researched to render visible how power is being exercised in knowledge
discourse and in whose interests it is being exercised (Habermas 1972).
Within discourse, discursive formations are the cultural codes and ways of organising
thought (including values) – in written and unwritten codes – that shape how we
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communicate and our attitudes; allowing some thoughts and actions but occluding
others (Foucault 1972). Discursive formations are about how what we communicate is
presented and read as likely, desirable, important, permissible, surprising, serious or
comprehensible (that is, evaluations) (Halliday 1985; Lemke 1998). In short, if we
understand the discourse we understand its authors’ values, what they aspire to and
the (taken for granted) assumptions they make revealing any unacknowledged
political or ideological agenda in the discourse.
Fuller (1995) argues that knowledge societies are not industrial societies permeated by
knowledge, but that knowledge societies are permeated by industrial values. Those
industrial values are inexorably associated with commercialised technology and
assumptions about the ability of technology to bring about change. Discourse theory
suggests that discursive formations in the dominant knowledge discourse will serve to
foreground the interests of those who benefit from that technical and commercial
expertise, the technocrats (McKenna et al. 2000). It also suggests that the values of the
technocrats will be expressed in discourse to effect particular ways of thinking and
behaving that promote their interests. This discourse is technocratic discourse
(McKenna et al. 2000). Discourse theory also predicts that insofar as power and
authority is exercised through discourse, the interests and values of ‘other’ groups will
simultaneously be rendered silent and their members unable to act to fully advocate
and implement their values and preferred practices. In technocratic discourse this is
done by invoking the authority, prestige and mystique of science. Discourse analysts
argue that specific value choices are ignored and undiscussed (Habermas 1972;
Lemke 1995, pp. 69-70). In addition, Lemke (1995, p. 71) shows that the value of the
outcomes of technocratic prescriptions are not adequately discussed either.
Technocrats only argue that what they claim is necessary not why it is necessary.
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In the context of this study it is relevant to note that technocrats are specifically those
who adopt “discourses of expert knowledge” and transform them into exhortations in
policy (Lemke 1995, p. 58), and to acknowledge the critique that while technocrats
are aligned with functionalist and instrumental values, aspirations and practices, they
tend to construct knowledge to primarily have commercial or industrial forms and
values, and to be an object that must be commodified (Gee et al. 1995, p. 10; Graham
in press). In terms of the WSIS it is the inclination and tendency of technocrats to
occlude and be insensitive to world-views and value systems outside their purview,
and to leave themselves politically, intellectually and ethically unchallenged to pursue
narrowly instrumental economistic outcomes that is of most concern (McKenna et al.
2000). I argue that under these conditions the full scope of what might be possible in
knowledge societies cannot be seen or realised.
3.1 KNOWLEDGE
Before returning to the topic of a narrow technocratic discourse, it is important to
spend some time discussing the sociological nature of knowledge. The social
epistemology of Fuller, and discourse theory discussed above clearly links
knowledge, language and power. In doing this it is suggested these things inter-relate
as a living system (Graham et al. 2001). More specifically, they demonstrate that
discourse (and therefore knowledge) arises from sets of social relations. An explicitly
inter-relational approach to the sociology of knowledge is therefore relevant to the
analysis of knowledge discourse. In doing this, the inter-relational approach is
concerned to demonstrate the generative mechanisms that create and diffuse
knowledge (Rooney et al. in press).
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In what follows I explain knowledge in a way that treats knowledge as inter relational
in which the inter relations provide the generative mechanisms for knowledge. These
elements are the points at which knowledge systems can be assessed and evaluated,
and where interventions can be made. To this end, I make four important observations
about the nature of knowledge.
First, a fundamental and inescapable observation about human knowledge is that it
necessarily implies the existence of people and societies. However, if knowledge is
fundamentally dependent on the existence of societies, societies are also dependent on
knowledge. The coherence of societies requires ideational and conceptual processes
between interacting agents (Hay 2001). A sociology of knowledge, therefore, must
account for the effects on knowing of the structures and organisation of social
relations and vice versa. What results in these interactions is some form of social
organisation and structure (e.g. hierarchies, social networks, communities, etc.). These
hierarchies, networks, and other forms of relations and positions are the social-
relational context of knowing.
Second, ideas are associative by nature and necessity. Ideas, theories, beliefs,
propositions, understandings, memories, etc. are connected to and depend on other
ideas, theories, etc. to be meaningful. The inter relational processes of knowing,
therefore, also occur at the intertextual and intersubjective level in which a
background of ideas, cognitions and hermeneutics held collectively by a set of
interlocutors is critical
Insofar as ideas, theories and beliefs form a shared phenomenological background in
which people think and act, this context is decidedly cultural. Culture can be defined
as a shared pattern of beliefs that lead to relatively stable patterns of behaviour and
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attitudes of groups held together by taken for granted assumptions about things such
as value, necessity and power. Knowledge, theories, beliefs, etc., therefore, are not
only phenomenological and social but are cultural, political and ideological.
Third, knowledge is often said to be situated (Lave et al. 1991) with its own
situational logic (Archer 1996). Moreover, knowledge has meanings and purposes that
are sensitive to the physical location of the knowers, the time in which they exist and
the history from which they have emerged. Importantly, therefore, the situation is a
place plus its associated history and physical objects (built and natural). In this way,
the physical aspects of situations include technology, and other elements of the built
environment including buildings, religious and cultural objects, furniture and even,
such things as the design and colour of those objects, and the natural environment or
geography (Burke 2000). Objects are of great importance to knowledge because at the
very least we develop beliefs about those objects (Bhaskar 1989, p.101), but also
because of them.
Finally, we must consider enactment, the process of acting on our knowledge,
intuitions, memories and so on. The ways in which we enact knowledge are
predictable and unpredictable, intentional and unintentional, rational and irrational.
Enactment focuses attention on the contradictions and paradoxes associated with the
use of knowledge, and it foregrounds the messy and in which we act with our
knowledge. For example, enactment is done more or less intentionally and
purposively. However, the degree to which one can be intentional is dependent on
ones conscious, intuitive, reflexive and strategic mental powers. Moreover, any
intentional decisions will likely involve both intuitive and explicit strategies; and that
both intuitive and explicit strategic choices are likely to also rely on incomplete or
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misleading information and imperfect knowledge. Also at issue is that the human
mind is boundedly rational (Simon 1955; 1991), and has finite biological limits to
how much it can learn, understand and use (Campbell 1974). The commonplace
results of these limitations are such things as errors of judgement and fact, indecision,
misinterpretation and so on. Enactment, therefore, is the fallibly intentional and
purposive political application of knowledge.
In addition, purposes are strongly directed by roles and positions (however voluntary
or involuntary they are) (Archer 1995, p. 201-3). Different people, because of their
different positions and roles, are also imbued with vested interests and different
degrees of power.
The picture of knowledge presented here is one that encompasses the full range of
human experience. To think of knowledge without considering memory, beliefs,
intuition, ideas, ideology, etc. is misguided and unrealistic. In addition, while
knowledge is important to creating and sustaining society and culture, society and
culture are important to creating and sustaining knowledge. Consequently, the links
between knowledge, society and culture must be considered. Moreover, when
knowledge is to be fostered to aid development, its political economy cannot be
ignored. It is also critical to observe that in this framework technology and economy
are important but encompass only a narrow part of the spectrum of factors that
animate knowledge systems. A knowledge policy that focuses only on this limited
part of the spectrum of knowledge’s generative mechanisms is at best incomplete, and
at worse incompetent and dangerous. Because of the complexity and infallibility of
enacting knowledge, it is not simply knowledge that is needed to create a knowledge
society but wisdom. Against a technocratic background, wisdom is needed because of
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its transcendent nature, its insightfulness and ethics (Baltes et al. 2000; Rooney in
press; Rooney et al. 2003b) are the critical human faculties for a knowledge society.
4.1 Computer Assisted Text Analysis
The data analysed in this study comes from a 1.3 million word corpus of knowledge-
related policy documents compiled from local, state, national, and supranational
institutions throughout the industrialised and industrialising world. Documents were
placed in the corpus because they relate to any of the inter-related topics of the
knowledge economy, knowledge society, information economy, information society
or the creative economy. Individual documents in the corpus were obtained from a
range of countries, including the United Kingdom, Australia, New Zealand, Canada,
USA, Greece, Denmark, Finland, France, Germany, Holland, Switzerland, South
Africa, Japan, Korea, Malaysia and India, and supranational policy organisations like
the OECD and the European Union. While the corpus was subjected to a grounded
analysis using computer assisted text analysis software, as each document was
sourced, the investigator read it for appropriateness and understanding. A deeper
understanding of the corpus has been developed since collection because it has
previously been analysed by the investigator using different techniques and theory,
and to answer other questions as part of a larger program of research into knowledge-
based economy discourse (Graham et al. 2001). Interpretation was also aided by the
investigators theoretical knowledge in relation to knowledge itself, political economy,
social theory and communication theory. The analytical method used in this study is
in degrees therefore both inductive and deductive.
The knowledge-related policy corpus was analysed using Leximancer. Leximancer is
a computer assisted text (content) analysis application that uses a machine-learning
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technique. The machine-learning process learns in a grounded fashion what the main
concepts in a corpus are and how they relate to each other. Content analysis can be
done as either conceptual (thematic) analysis or relational (semantic) analysis.
Leximancer does both, identifying concepts in the corpus and how they interrelate. In
identifying concepts and showing how they interrelate, Leximancer uses word
frequency and co-occurrence counts as it basic data. Leximancer builds its analysis by
using the frequency data and data about the co-occurrence of concepts to produce a
concept co-occurrence matrix. Once a concept has been identified Leximancer then
builds a thesaurus of words that are closely related to the concept thus giving the
concept its semantic or definitional content.
A picture of the relational (semantic context) characteristics of the concepts is created
in two important ways. First, data is created relating to the direct co-occurrence of
concepts. Direct links between concepts are measured establishing the strength of
relations between concepts. The more times a concept occurs directly with another,
the stronger the relationship. Second, a more complex picture emerges when data
about what is semantically related to a concept is related to other concepts and their
co-occurring words. Thus Leximancer can compare a concepts thesaurus with other
concepts’ thesauri. In this way indirect links between concepts are accounted for,
meaning that a significant semantic relationship can exist between concepts even
when there are, in the main, only indirect relationship between them. Overall, then,
Leximancer rank orders concepts, and tells the investigator about the strength of
association between concepts and semantic similarity between concepts.
Finally, Leximancer stochastically calculates a map of the concepts in the corpus.
This visualisation technique enables the investigator to see, in a global representation,
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what are the important concepts in the corpus and relationships between these
concepts. Hence, concepts that are directly related but are not necessarily strongly
semantically linked and can be far apart on the concept map while concepts that are
strongly semantically related will be close to each other on the concept map.
Therefore, concepts that occur in very similar semantic contexts tend to form clusters.
The map is then used by the investigator to present an overall representation of the
corpus and to guide interpretation.
The investigator can also ‘drill’ down through a concept, into its thesaurus of words,
and then directly into the chunks of text where those concepts and words are found.
This allows the investigator to easily interrogate the text and interpret it in light of his
or her own reading of the corpus and to apply various linguistic analytical techniques
such as discourse analysis.
In using machine-learning to do the above analysis, Leximancer builds a library of
concepts in the text in a grounded fashion according to a set computational criteria.
Leximancer was asked to find 80 concepts; stop words were removed automatically;
three sentence blocks were set as the boundaries for measuring contextual
relationship; bi-gram sensitivity was set at moderate (4); and the threshold for
establishing if a word is admissible as an additional concept seed (the learning
threshold) was set at normal (14).
An important feature of this kind of analysis is its reliability. Leximancer addresses
reliability in two ways. First, it affords stability and second, reproducibility. Stability
in Leximancer is equivalent to intercoder reliability. That is, the automated and
deterministic machine-learning phase will be highly consistent no matter how many
times a corpus is processed and reprocessed (coded and recoded) by the application. It
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can therefore be said that Leximancer has a high level of coding stability.
Reproducibility in the context of Leximancer is seen in its consistency in classifying
text given the same coding scheme. Consistent classifying manifests in a consistently
constructed stochastic concept map. In other words if the map is calculated and
recalculated a number of times the researcher can inspect the each new map for its
consistency with previous maps. If maps are dissimilar the researcher can alter any of
the computational criteria being applied to the corpus in an endeavour to make the
map consistently reproducible. Leximancer produced highly stable maps for this
study.
Additional analysis was performed using Pajek social network analysis software. The
Leximancer map data file was fed into Pajek to create a network map that displays the
direct links between concepts in greater detail than does Leximancer. Pajek was set to
draw a network with all links with a value of less than 0.2 removed. This was done to
remove the weakest links making the network more easily readable.
5.1 Representing the Corpus
Because public policy (including economic policy) should contribute to making a
better society and because knowledge-related policy (including that with an explicit
economic or technological agenda) should seek to make a better society through
knowledge, it is reasonable to expect that any knowledge-related policy aims to
address a broad range of social, cultural, environmental and economic issues and
interests. In general terms, then, achieving knowledge society or economy status
might be found by, for example, making a society more knowledgeable and wise
about business, culture and the environment. This position is reinforced in light of the
sociology of knowledge presented above. However, based on such assumptions and in
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light of the questions that discourse theory raises it is reasonable to assume that the
knowledge-related policy corpus should be inspected thematically (conceptually) and
relationally (semantically) to determine if a broad agenda like this exists within it.
Using Leximancer, thematic analysis is facilitated by inspecting the rank ordered
concept list and then spending some time reviewing the thesauri of words that define
the concepts identified (Table 1). The thesaurus for a concept shows the most strongly
(directly and indirectly) related words to the concept they are defining.
Table 1. Top 20 ranked concepts
Concept Absolute count
Relative count
Thesaurus
service 2585 100% networks, information, telecommunications, e-commerce, internet, infrastructure, access, government, public, provision,
information 2561 99% technology, service, society, government, development, public, internet, e-commerce, networks, communication
e-commerce 2276 88% service, internet, government, should, business, information, networks, access, public, development
internet 1842 71.2% service, e-commerce, networks, information, access, government, public, should, technology, business
technology 1535 59.3% information, research, regulations, medical, reproductive, development, related, science & technology, service, should
government 1307 50.5% information, e-commerce, service, should, internet, public, online, industry, technology, development
should 1281 49.5% e-commerce, service, technology, government, public, information, internet, related, law, medical
networks 1200 46.4% service, telecommunications, internet, information, infrastructure, access, e-commerce, public, provision, development
public 914 35.3% service, information, networks, should, technology, e-commerce, internet, government, policy, telecommunications
development 847 32.7% information, technology, service, research, e-commerce, networks, government, internet, science & technology, public
business 792 30.6% e-commerce, information, service, assets, intangible assets, internet, reporting, government, industry, should
access 778 30% service, internet, networks, information, e-commerce, public, telecommunications,
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government, should, infrastructure industry 774 29.9% industries, sectors, market, products, rate,
service, e-commerce, information, countries, , manufacturing
market 736 28.4% service, industry, products, sectors, countries, industries, goods, rate, manufacturing, basic
telecommunications 632 24.4% service, networks, infrastructure, provision, public, access, regulatory, market, competition, member
research 543 21% technology, information, development, science & technology, should, medical, regulations, networks, studies, related
products 543 21% industry, market, industries, rate, sectors, goods, service, countries, manufacturing, basic
policy 522 20.1% information, public, government, technology, should, competition, service, development, case, framework
infrastructure 511 19.7% service, telecommunications, networks, provision, should, public, information, access, regulatory, development
international 490 18.9% e-commerce, internet, should, law, service, information, countries, rules, networks, government
Of the 20 most important concepts, governance (government, law, regulation, public,
policy), technological (e-commerce, networks, telecommunications and infrastructure)
and commercial (business, industry, market, products, service) concepts feature most
prominently, and are clearly central to the concerns of the authors in the corpus, while
less room is given to cultural and social concerns (public, access). Given that it is a
corpus of policy-related documents, the emphasis on governance is not surprising.
However, the rather sharp focus on technology and business is notable and is
consistent with arguments about technocratic discourse. Service, e-commerce,
internet, technology, networks, telecommunications, infrastructure, business, industry,
market and products are all highly ranked concepts and also feature in the thesauri.
Concepts that appear to be social policy oriented such as access, public and medical
occur in the thesauri and concept list, and so they are important but they are not the
most prominent. Concepts that might relate to culture, intellection and education also
appear outside the top 20 concepts (intellectual, communication, environment,
cultural, learning). Some concepts that at face value look social policy oriented are not
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unambiguously so. For example, the concept, access, is primarily about access to
ICTs (internet, networks, information, e-commerce, infrastructure) rather than directly
about access to, for example, education, welfare and cultural activities, all things a
theory of knowing suggest might also be of concern in knowledge-related policy. I
will return to this point below.
A perspective on how concepts are semantically contextualised is obtained by
interpreting the relational (semantic) representation of the data using Leximancer’s
concept map. To make the concept map more understandable in the first instance, the
proportion of concepts displayed has been reduced from 100% (of 80 concepts) to the
top 8% (Map 1). This is the lowest level at which a number of discernable semantic
clusters has formed. Reduced to this level, only the 27 most important concepts are
shown. While more clusters will emerge at a higher level of resolution (Map 2), these
clusters can be considered indicative of the most important discursive semantic
markers in the corpus.
Map 1 (at 18%)
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By virtue of their proximity to each other, we can say that clusters A, B and C are
closely semantically related, while cluster D is semantically distant from the others.
Cluster D is clearly concerned with business and commercial issues (business,
products, industry, markets). Cluster A appears to be concerned with innovation
policy (research, technology, policy), and cluster B is concerned with policy and
government (policy, regulation, government, law). Cluster C is concerned with
telecommunications infrastructure (telecommunications, infrastructure, networks).
Based on this, we can confirm that the primary semantic categories of the corpus are
business, governance, and technology. In addition, we can say that the Business
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D
A
B
C
cluster is less meaningfully (less semantically) connected to the other clusters. At this
level of resolution there is no cluster that has knowledge as its central focus.
Much more can be discerned from the concept map when the resolution is set to 54%
(Map 2).
Map 2 (at 54%)
At this level of resolution much more of the data is represented on the map and it
therefore provides a more detailed view of the corpus and the opportunity to refine
interpretations. To this end, not only are there more concepts on the map but there are
three new semantic clusters; (e) Internationalisation (country, internationalisation); (f)
Knowledge & Skills (knowledge, skills, education); and (g) Finance (finance, capital,
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f Knowledge & Skills
g Finance
A Innovation Policy
B Law & Policy
C Telecoms Infrastructure
D Business
e Internationalisation
Business ICT
GovernanceEnactment
assets). It is also possible to label the original clusters; (A) Innovation Policy, (B) Law
and Policy, (C) Telecommunications and (D) Business. With the additional data it is
now possible to characterise the general orientation of each of the four quadrants of
the map. The top left quadrant is concerned with issues of Business (business,
finance), the top right quadrant is concerned with issues related to ICTs (e-commerce,
internet, online, telecommunications), the bottom right quadrant is concerned with
Governance (policy, law, rules, government), and the bottom left quadrant is
concerned with Enactment (skills, work, science and technology, progress, creation).
This characterisation of the concept map says much about the key concerns of policy
makers in relation to knowledge, reinforcing the view that they privilege a business
and technology agenda. Clearly, policy makers see an important role for technology in
achieving their goals. This is well illustrated if we look at the ICT, Governance and
Enactment quadrants where there is considerable overlap between the Innovation
Policy, Law and Policy, and Telecommunications Infrastructure clusters. Governance
concerns are semantically linked to ICT concerns (communications, infrastructure,
intellectual property, market, regulation), and science and technology more generally
(science_technology, technology). It is suggested again that policy makers see
technology as the conduit for delivering benefits to their communities. This raises
concerns about assumptions based on an attitude resembling technological
determinism (Feenberg 1991). This will become more evident below when I examine
specific excerpts from the corpus.
Enactment covers what the corpus regards as the most important way to enact
knowledge. Tellingly, this quadrant is heavily biased towards vocational skills
training and to technological development in the economy. It is concerned with
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research but more particularly industrial research and development. This feature of the
corpus will become more obvious as I deal with specific examples of text from the
corpus. It is also important to note that while medical research is featured, social
scientific and humanities research is not. It is also important to note the semantic
distance between the Knowledge and Skills cluster to the other clusters.
In understanding semantic distance, it is instructive to consider how concepts and
concept clusters are inter-linked. Considering how concepts are linked demonstrates
much about how the authors’ of the corpus have reasoned the connections between
concepts. Indeed, it says much about how they (fail to) argue their cases, and what
they assume and ask us to take for granted. To do this I have employed Pajek social
network analysis software to specify the details of the links between concepts. Apart
from a 90 degrees axis rotation, the Pajek network graph (Map 3) is broadly consistent
with the Leximancer concept map and it amplifies several critical features of it. The
most important Leximancer semantic clusters can be discerned in the graph and links
between concepts are plotted.
Map 3. Conceptual Network (links valued at less than .2 removed)
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The first of the amplified features is the considerable level of cross linking between
the Telecommunications Infrastructure, Law and Policy, and Innovation Policy
clusters. This is indicative of the level of direct association between these clusters
made in the text. Specifically, repeated claims are made that government has a role to
play in fostering the development, provision and use of technology. This attitude can
be explored by examining exemplars in the corpus. The following excerpt illustrates
some of the consistently made claims in the corpus.
Looking to the near future, we can envisage an Australia where: The processes of work, commerce, learning, education and training, social interaction and government are being transformed by communication and information technologies; in which all Australians are able to take part in the opportunities brought home by the global information economy. All Australians, particularly those outside the major cities, have unprecedented access to communications, information, government services such as health and education, entertainment and culture, goods and services from around the country and the world; and have the skills and knowledge to access what they need online, and to make creative contributions to the stock of ideas and products available. (CITA1.txt~1.html#S1_112)
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Telecoms Infrastructure
Business
Innovation
Knowledge & Skills
Finance
Law & Policy
Demonstrated here is the view that government must work harder for technologizing
the community. Specifically, technology transforms the community, creates
opportunities and access, and makes people creative. This is highly technologically
deterministic; the claim is that it is technology that stimulates desirable outcomes.
How technology does this is not explained and what else is needed to achieve these
outcomes is not seriously considered. It assumes that technology’s importance is self-
evident. The same document makes claims about the role of technology in more
specific terms. It sees the role of education policy largely in terms of providing ever
changing technology skills for the information economy.
Vocational education and training is a key hub into the Australian community and into industry. Its challenge is to harness its significant potential to provide flexible responses for constantly changing learning environments. To be effective and provide a foundation to foster the information economy, training organisations will require the advanced information infrastructure to develop, trial and deploy applications, content and services for new technology and communications. (CITA1.txt~1.html#S1_195)
The basic assumption, that vocational training is good for the community and
industry, is highlighted in the opening sentence. This is followed by a nebulous
statement about potential, flexibility, change and learning, which has an unexplained
connection to the next sentence that advocates the necessary deployment of new and
advanced technology. The vagueness of the argument notwithstanding, it can be
interpreted as a case where we are asked to take for granted that vocational training,
particularly if it employs new technology, will make creative employees for the
information economy. Again, it is taken for granted that one thing leads to another.
The same strategy is evident in the next excerpt.
In order for the education system to be adapted to the requirements of the 21st century, the government promotes the familiarisation of students with computers and multimedia, in all education levels, and trains teachers in the new technologies. (GREECE1.txt~1.html#S1_45)
The document continues by claiming:
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In the digital age, economic competition is increasingly based on technology and knowledge. (GREECE1.txt~1.html#S1_45)
The technological imperative is repeated here. Knowledge of computers, multimedia
and new technologies provided by the education system are required because
competitiveness (in business) is based on technology and knowledge. Much is left
unstated here. What are the grounds for making these assertions? What else could the
education system be concerned about? Why is economic competition so important?
And why are technology and knowledge regarded as essential factors for improving
competitiveness?
The Business cluster is notable for the fact that the concepts in it are tightly
interlinked suggesting that claims being put forward here are internally consistent.
However, judging by the moderate level of outlinking to other clusters we are being
asked to accept the central role of business in a knowledge society using a limited
range of claims that provide even less explanation of how benefits are delivered than
other clusters do. The following excerpt is quite matter of fact about the necessity for
government to support business needs and promote the idea that competition and
market forces are intrinsically good.
[T]he Administration successfully concluded the WTO Basic Telecommunications negotiations, which will ensure global competition in the provision of basic telecommunication services and will address the many underlying issues affecting online service providers. During those negotiations, the U.S. succeeded in ensuring that new regulatory burdens would not be imposed upon online service providers that would stifle the deployment of new technologies and services. As the WTO Agreement is implemented, the Administration will seek to ensure that new rules of competition in the global communications marketplace will be technology neutral and will not hinder the development of electronic commerce … The Administration will also seek effective implementation of the Information Technology Agreement concluded by the members of the WTO in March 1997, which is designed to remove tariffs on almost all types of information technology. Building on this success, and with the encouragement of U.S. companies, the administration is developing plans for ITA II, in which it will to seek to remove remaining tariffs
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on, and existing non-tariff barriers to, information technology goods and services. (USframe.txt~2.html#S1_274)
Global competition to assist U.S. companies to sell technology, telecommunications
services and conduct e-commerce by deregulating global markets are the central
concerns here. The core of the argument is that the rules of the global marketplace
should be technology neutral (to aid the development of new US technologies for
electronic commerce). While we are being asked to accept the possibility of some
kind of value-free rules (a logical impossibility), we are also being asked to accept the
authors’ values (competition, deregulation, market economics). The tenor of argument
here is therefore far from neutral. Indeed, this excerpt is exemplary of the market and
globalisation mantras of neoliberal ideology. This excerpt demonstrates a strident and
rigid ideological stance that competition, deregulation and technology go hand in
hand, and that unfettered technological change, driven by business is desirable.
Specifically, it argues for change to be driven exclusively by market forces as a
simple and straight forward and certain way forward. There is no tolerance of a messy
enactment, filtered through cultural, social and situational contingencies; such things
are simply written out of reality. It is a supreme example of technocratic discourse.
The third main feature is the relationship of knowledge to other concepts. Knowledge
is decidedly unlinked in the map. It should be of concern that concepts in the
Knowledge and Skills cluster are only weakly inter linked, and it is also of concern
that the Knowledge and Skills cluster is not highly linked to the other clusters. This
suggests that the ways in which knowledge relates to other concepts is not explained
and perhaps is not understood. This lack of explanatory commitment and ability is a
concern and is well illustrated in the following:
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As their careers unfold, high-school teachers should also return periodically to the non-academic workplace to keep abreast of changing work and skill requirements. (canada1.txt~6.html#S1_1058)
The use of the word, should, is instructive here. Precisely why all teachers should do
this is not canvassed. However, the implication that teachers would learn more about
the needs of business by doing this is clear and so too is the assumption that the main
purpose of schooling in a knowledge-based economy is to train people for work. It is
taken for granted that this kind of thing is necessarily good and that it is all that is
necessary for schools to have adequately contributed to knowledge. However, that
teachers might also be well served learning other things to do with non commercial
spheres of life is not presented. Neither is the possibility that students might also be
well served learning non vocational things or that it is business that should conduct
vocational training presented. Non commercial elements of education are not seen to
be the most important. The taken for grantedness and the degree to which the
underlying claims are implied by the authors’ is quite extreme. The next excerpt
displays a higher order of implied logic still, to the point that even the implication is at
best a perfunctory one and an even narrower view of knowledge.
Cyber Korea 21 aims to create the framework of a knowledge-based society and to improve national competitiveness and the quality of life to the level of the advanced nations. By 2002, the proportion of the knowledge-based industry in GDP will be similar to that of OECD member nations and Korea will become one of the top ten advanced information societies in the world. Early completion of information infrastructures is essential to the solid foundation of the information society. By 2002, the speed of the Internet services throughout Korea will be accelerated by one hundred times than it is available now. Every information system will be based on the Internet to pursue the global standard. In order to make Koreans the best computer users in the world, opportunities for computer classes will be widened to include all members of the society. The number of Internet users will pass ten million by 2001. (korea2.txt~1.html#S1_15)
According to the logic of this excerpt becoming a knowledge-based society involves
no more than having many skilled computer users and information infrastructure. The
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agenda is about being an advanced nation and this is measured only in terms of
technological capacities. Knowledge is given no meaning outside a purely
instrumental framework. Again, it is not made clear what the logic of this argument is.
Indeed, this excerpt resembles a very rudimentary sketch of a recipe. The thinking is
superficial and technocratic in the extreme, and displays a serious lack of explanatory
commitment that is almost a caricature of taken for grantedness.
This analysis shows that the Knowledge and Skills cluster is semantically isolated
suggesting that the authors of the corpus have not seriously considered the nature of
knowledge and how it is linked to the social, cultural and economic realms. Going
further, while knowledge might be the espoused central concern, the real concerns of
the corpus are technology and business. Knowledge is simply a convenient vehicle to
convey vested interests. The corpus is also interesting for its lack of accommodation
of social and cultural aspects of knowledge. Even if one justifiably seeks economic
benefits from knowledge, because knowledge is profoundly based in social and
cultural processes the economic benefits will be dependant on those social and
cultural foundations. In this situation even the economic planner who recognises the
economic importance of knowledge must consider and discuss the social and cultural
fundamentals.
6.1 Implications for the WSIS
While there are examples in the corpus of concern for issues such as culture, art, the
environment and social policy that are normally outside the scope of technocratic
discourse, it is clear that its central focus and its general concerns are nevertheless
technocratic in nature. It is also important to specifically note that the corpus does not
see knowledge as valuable in its own right and that presents no clear understanding of
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what knowledge is. The value and nature of knowledge is presented as a function of
its ability to contribute, instrumentally, to technology and the economy. What are
WSIS members to make of this and how can it help them make their case for
development along knowledge economy and knowledge society lines? There are three
ways in which this research is important to WSIS objectives.
First, knowledge is political and we must make a choice about what politics we want;
the politics of emancipation or the politics of technocracy. Politics and power cannot
be ignored when one is developing policy to foster the development of a knowledge-
based economy or knowledge society. I argue that a policy agenda for knowledge
must make an explicit choice about what kind of politics will infuse it. Knowledge-
related policy is well positioned to adopt a politics of emancipation, of equity, cultural
enrichment and of wisdom. It is also important to emphasise the view that adopting
such a political stance is not to necessarily exclude important concerns in relation of
economics, commerce and technology. While it may often seem that one must choose
between culture and commerce, there is no reason to do so. What is clear is that the
dominant discourse has as one of its effects to encourage us to see the world in black
and white thus channelling resources in a particular direction rather than in many
directions (Graham in press). My analysis cautions that technocratic discourse
threatens democracy and national (cultural) sovereignty in a globalising world by
occluding that which is beyond its immediate narrow interests. Technocratic politics
is therefore problematic for participative and representative democracy because it
represents the interests of business and technology rather than wisdom, culture, the
environment and the ‘other’.
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Second, a sociological theory of knowing can impose a discipline on policy analysis
and formulation that renders what is occluded by the dominant discourse more visible
and more discussable. WSIS members can better position themselves is through the
possession of a sound and comprehensive conceptual framework describing the
sociology and political economy of knowledge. Such a framework provides a
discipline to guide policy analysis, formulation and implementation, one that enables
us to test knowledge-related policy for its completeness of perspective and its politics.
If we are serious that knowledge is important in its own right we must deal with it in
its own right, not as an epiphenomenon or a smokescreen as it is treated in the
dominant discourse. Using the framework presented here we are reminded that social
networks and other social structures, and interpersonal and intergroup relations must
be considered when thinking of knowledge and society. We are also reminded that
reflexivity, creativity and culture are essential aspects of knowing and that the nature
of individual knowers’ skills, wants, and ethics must be considered. Furthermore,
while it is clear that it is easy to see a role for technology in knowledge-related policy,
what is more difficult to see is that such things as the nature of places, history,
landscapes and cultural objects are critical to knowledge.
Third, the theory set out here makes clear the messy nature of enacting knowledge and
cautions us that the implementation of knowledge-related policy is no simple task. It
is also useful to be reminded that how knowledge is enacted remains unacknowledged
in the dominant knowledge-related policy discourse. That the enactment of knowledge
is unacknowledged for its messy and paradoxical (intentional/unintentional,
rational/irrational) character; its problems in relation to imperfect knowledge and
bounded rationality; and the effects of the voluntary/involuntary nature of roles,
positions and power on it is problematic. Importantly, this messiness actually enriches
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life and should be valued rather than narrowed, confined and limited to the concerns
of technocrats. Discourse about knowledge in the WSIS is not technocratic and
unbalanced, it possesses more wisdom than that, and WSIS members have, therefore,
an opportunity to progress towards a knowledge society if they do not succumb to
technocratic discourse. This is an opportunity that developed nations may not now
have. They appear to be on a trajectory towards a technocratic society that eschews
wisdom. Moreover, developing countries may find they are better positioned than
developed countries to draw on wisdom as a resource for creating a better future.
In summary, WSIS members can avoid the failures of technocracy and better
articulate their arguments against technocratic imperatives if they have a conceptual
framework that explains the dynamics of knowledge and of technocratic discourse
while providing a yardstick against which knowledge discourse can be assessed.
Moreover, such a framework enables WSIS members to explain their positions, needs
and strategies, and remind them that they should make the explanatory commitment
that is missing (for ideological reasons) in technocratic discourse. A knowledge
politics that is emancipatory in nature is more likely to result if it is informed by a
framework such as that presented here.
ReferencesArcher, M.S. Realist Social Theory: The Morphogenetic Approach, Cambridge
University Press, Cambridge, 1995.Archer, M.S. Culture and Agency: The Place of Culture in Social Theory (Revised
Edition), Cambridge University Press, Cambridge, 1996.Baltes, P.B., and Staudinger, U.M. "A Metaheuristic (Pragmatic) to Orchestrate Mind
and Virtue Towards Excellence," American Psychologist (55:1) 2000, pp 122-136.
Bhaskar, R. Reclaiming Reality: A Critical Introduction to Contemporary Philosophy, Verso, London, 1989.
Burke, P. A Social History of Knowledge: From Gutenberg to Diderot, Polity, Cambridge, 2000.
28
Campbell, D.T. "Evolutionary Epistemology," in: Language, Development and Culture, D.T.E. Campbell (ed.), Wiley and Sons, New York, 1974, pp. 413-463.
Chomsky, N. Language and Mind, Harcourt Brace Jovanovich, New York, 1968.Dissanyake, W. "The Need for the Study of Asian Approaches to Communication,"
Media Asia (13:1) 1986, pp 217-227.Feenberg, A. Critical Theory of Technology, Oxford University Press, New York,
1991.Foucault, M. The Archaeology of Knowledge, ((A.M.T. Sheridan Smith) Tavistock,
London, 1972.Foucault, M. Discipline and Punish: The Birth of the Prison, ((A. Sheridan) Penguin,
Harmondsworth, 1979.Freire, P. Pedagogy of the Oppressed, Continuum, New York, 1983.Gee, J.P., and Lankshear, C. "The New Work Order: Critical Language Awareness
and "Fast Capitalism" Texts," Studies in the Cultural Politics of Education (16:1) 1995, pp 5-19.
Graham, P. "Analysing Policy Values in a Knowledge Economy," in: The Knowledge Economy Handbook, D. Rooney, G. Hearn and A. Ninan (eds.), Edward Elgar, Cheltenham, in press.
Graham, P., and Rooney, D. "A Sociolinguistic Approach to Applied Epistemology: Examining Technocratic Values in Global "Knowledge" Policy," Social Epistemology (15:3) 2001, pp 155-169.
Habermas, J. Knowledge and Human Interests, ((J.J. Shapiro) Heinemann, London, 1972.
Halliday, M.A.K. An Introduction to Functional Grammar, Edward Arnold, London, 1985.
Hay, C. "What Place for Ideas in the Structure-Agency Debate? Globalisation as a 'Process Without a Subject'" World Wide Web 2001. Accessed 24/11/03.
Lave, J., and Wenger, E. Situated Learning: Legitimate Peripheral Participation, Cambridge University Press, Cambridge, 1991.
Lemke, J.L. Textual Politics: Discourse and Social Dynamics, Taylor & Francis, London, 1995.
Lemke, J.L. "Resources for Attitudinal Meaning. Evaluative Orientations in Text Semantics," Functions of Language (5:1) 1998, pp 33-56.
Lerner, D. The Passing of Traditional Society: Modernizing the Middle East, Free Press of Glencoe, New York, 1958.
McKenna, B.J., and Graham, P. "Technocratic Discourse: A Primer," Technical Writing and Communication (30:3) 2000, pp 219-247.
Rogers, E. Communication and Development, Sage, Beverly Hills, 1976.Rooney, D. "Wisdom, Values & Creativity in a Knowledge Society," in: World
Summit on the Information Society, How should the Smart State Respond, J. Servaes (ed.), School of Journalism and Communication, University of Queensland, Brisbane, in press.
Rooney, D., Hearn, G., Mandeville, T., and Joseph, R. Public Policy in Knowledge-Based Economies: Foundations and Frameworks, Edward Elgar, Cheltenham, 2003a.
Rooney, D., McKenna, B., and Hearn, G. "The Knowledge-Based Economy: Savant or Sage," Paper presented to the Knowledge and Economic and Social Change: New Challenges to Innovation Studies Conference, Manchester, 2003b.
29
Rooney, D., and Schneider, U. "A Model of the Material, Mental, Historical and Social Character of Knowledge," in: The Knowledge Economy Handbook, D. Rooney, G. Hearn and A. Ninan (eds.), Edward Elgar, Cheltenham, in press.
Schiller, H. Mass Communication and American Empire, A.M. Kelley, New York, 1969.
Simon, H.A. "A Behavioural Model of Rational Choice," Quarterly Journal of Economics (69) 1955, pp 99-118.
Simon, H.A. "Bounded Rationality and Organizational Learning," Organization Science (2) 1991, pp 125-134.
Welbourne, M. Knowledge, Acumen, Chesham, 2001.
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