IMPLEMENTACIÓN DEL MÓDULO ESTADÍSTICAS DE TRÁFICO

12 _{For a definition and examination of phenomenology see section '3:2:1:2 Phenomenological Analysis'.}

in order to identify their weaknesses.

which research is carried out.27 Thus, feminist standpoint epistemology actually

radicalizes the Enlightenment project by producing an objectivity greater than the

androcentric Enlightenment was able to produce.28 Objectivism, then, provides an

inadequate foundation for policy analysis, and is rejected as a theoretical framework.

I now turn to a critique of positivism.

1:2:2 Positivism

Recalling the discussion of positivism in section 1:1:2:1, the term is used as a

general legacy rather than specific sense. It refers to a refusal to treat as knowledge

anything that cannot be empirically demonstrated. This empirical orientation is

manifest in a need to reduce data to quantifiable terms. It follows from this that a

positivist methodology is the only way to produce ‘real’ knowledge.

The preceding critique of objectivism ought to be sufficient to destabilise any

notion of knowledge being simply accessible to the ‘correct’ methodologies. There is

no such thing as a pre-conceptual ‘fact’; all facts are socially situated. Even simple

data that are easily quantifiable assume a social location and are built on particular

assumptions. Deciding what, exactly, will count as appropriate data, is an act of pre-

judgment where exclusionary and inclusionary decisions are made.29 Positivism is

27 _{DeWalt (1994) provides some interesting examples of combining indigenous knowledge systems with} scientific knowledge systems. DeWalt argues combining knowledge systems does no automatically guarantee improved or more useful knowledge, but he calls for more effective and creative interactions between these systems so as to enhance this possibility.

28 _{I do not infer that feminism shares all the goals of the Enlightenment, but simply that, in this respect,} standpoint epistemology goes further, and thus continues, the Enlightenment search for objective knowledge.

29 _{There are two points here. First, the fact that human beings, for example, need air to breathe cannot} rationally be denied. What potentially could be denied is the theory which explains why we need air. Perhaps a better explanation could be generated by approaching the question from a different angle. Therefore, what I deny is the idea that humans can have access to unmediated reality – the world as it ‘really is’. This is fiction, not because there is no ‘real world’ out there, but because it is always mediated through particular social locations. For this reason, reflexivity is essential in all epistemological endeavours for it will help produce ‘better’ knowledge,

flawed because it nurtures a dogmatic quality which resists any knowledge claim not

empirically grounded. The critical point here is not that data quantification cannot be

useful in scientific endeavour. Rather, the unwarranted exclusion of other forms and

methodologies of knowledge production results in serious limitations (such as

reduced objectivity) of positivist methods. For this reason, positivism, but not

empirical quantification per se, is rejected as a valid process of knowledge generation.

The positivism I reject is exclusionary in its basic assumption that knowledge equals

positive empirical data. It is the general legacy and orientation I reject, but this ought

not be construed as a rejection of empirical methodologies in general.30Nevertheless,

some further comments are necessary to understand the relation of empirical research

to a discursive epistemology.

Empirical knowledge is confronted with an unresolved question of logic. Such

Knowledge is supposedly derived from one’s personal experience of an object. The

problem is that although we may be certain about our experience, we cannot be

certain about what another person experiences, for those experiences are fundamentally

private. Diesing (1991) poses this problem by assuming we see a black crow in front

of us (pgs. 11-12). But how, he asks, are we to be sure our friend sees the same thing,

or that she is telling the truth? We cannot ‘test’ her sense experience for it is

inaccessible to us. We are left relying on some form of intermediary, namely

communication. There is no way logic can resolve this problem, so Diesing concludes

“Science is founded on nearly meaningless statements” (1991:12).

That is, knowledge which assists human wellbeing. On this notion of assistance to human wellbeing, see Rorty(1982) 30 _{I do not address the various theories of scientific knowledge production in this thesis, for it lies somewhat}

tangential to my primary purpose of articulating communicative rationality. Diesing (1982; 1991) provides

interesting accounts of these theories in relation to policy science and social science respectively.

ends or an assessment that they are not technically achievable (at least without further modification to either ends or procedures). For instrumental rationality, the ethical status or value of ends lies outside its analytic scope (Shapiro, 1981:7). But ends are essentially value statements, preferred courses of action and outcomes. Often, these end values lie obscured beneath a wealth of technical data and expert opinion, remaining effectively removed from critical public debate. More importantly is the fact that values which make up chosen ends represent particular values. Almost inevitably, they are the values of the powerful and elite. The problem is not that certain values as opposed to others are being served, but that the discourse of scientific impartiality serves to mask this fact (Rule, 1978:18). Given that instrumental rationality is indifferent to ends, it needs to be subordinate to an ethic which can determine the social desirability of the particular goals.34

1:2:3:2 Inadequate Analytic Methodology

Central to instrumental rationality's usefulness is its strategy of 'decomposing' problems into their fundamental components (Dunn, 1981:21). This is part of the 'analycentric' perspective predominant in policy analysis (Bührs and Bartlett, 1993:16; Dryzek, 1990a:61). Dryzek (1990a) puts it this way:

Instrumental rationality goes hand in hand with an analytic sensibility, the idea that complex phenomena are best understood through intelligent disaggregation into their component parts (pg. 6, emphasis in original).

By breaking down the problem or situation under analysis into more basic units, the analyst is able to locate opportunities for solution building. Many problems appear

34

This point is elaborated more fully in section '2:1:2'.

to be so full of complexity that it is not cognitively possible to apprehend the