View Full Version : Science!

josef k.
07-06-2009, 05:43 PM
Serres argues that the Age of Enlightenment was very instrumental in categorizing as irrational any reason not formed by science. He holds the Enlightenment responsible for the split between literature and science, which favors a definition of rationality supported exclusively by scientific research. The epistemological rupture between literature and science took place in the eighteenth century, which sought to label as irrational anything that was not science. In other words, science aimed at taking over the totality of reason relegating literature to the irrational or the imaginary. But as he states:

I maintain that there is as much reason in the works of Montaigne or Verlaine as there is in physics or biochemistry and, reciprocally, that often there is as much unreason scattered through the sciences as there is in certain dreams. Reason is statistically distributed everywhere; no one can claim exclusive rights to it (Serres, 1995b, p. 50).

VIA (http://www.ijea.org/v3n3/)


"Serres' passionate skepticism and rejection of the traditional French philosophy of Critique—the rational separation between nature and culture in the line of Descartes, Marx, and Sartre (see Latour, 1988;Wesling, 1996)—have been condemned both by postmodernists and traditional empiricists. <strong>Katherine Hayles says that Serres is confused and needs a logic lesson; Luc Ferry writes that Serres is a dangerous prophet who might unite with other mystagogues, get power, and overturn the order of modernity; Jean Baudrillard, one of Serres' fiercest critics, argues that Serres should be almost admired as a small morbid symptom of a doom to be welcomed (Wesling, 1996, p. 1999)</strong>"

07-06-2009, 06:46 PM
Could "reason" or "rationality" be the wrong word? Could it be that science is actually our best method of "drifting" "toward" "universality"?

josef k.
07-06-2009, 06:52 PM
Serres suggests that there is no best method, and perhaps no method at all.


His "method" is actually an "anti-method," as Harari and Bell (1982) point out, precisely because Serres is opposed to the idea of linear progress and development as exemplified in following a series of methodological steps.

Method is the illustration of a given type of knowledge through the set of results that the method can produce. But the term method itself is problematic because it suggests the notion of repetition and predictability—a method that anyone can apply. Method implies also mastery and closure, both of which are detrimental to invention. On the contrary, Serres' method invents: it is thus an anti-method. (Harari & Bell, 1982, p. xxxvi, authors' emphasis)

07-06-2009, 06:52 PM
I recently chatted with some people taking the same quant methods module. We kind of agreed that quant methods involves a kind of magic, whereby one comes up with a hypothesis, waves at some data with the magic wand of SPSS (or whatevs), produces a couple of statistics and triumphantly shouts "ta-da"!

They were of the opinion that qualitative methods is the way to go, but that seems to me to assume away the problem, which is one of knowledge: what are you trying to say with what, and how confident can you be in your conclusions. Rigour can be its own kind of mysticism, of course, but I find that it often makes me think carefully about what I am writing.

josef k.
07-06-2009, 06:59 PM
I'm interested most of all in the rigour of rhetoric... including the rhetoric of quantitative methods, other kinds of methods... the rhetorical effects they are designed to achieve.

07-06-2009, 07:13 PM
From one perspective, it's all rhetoric, since the issue is not even necessarily whether one has found a relationship or not, but rather whether one can manipulate a dataset such that one can produce a statistic, like a p-value, that says, "this relationship has significance" to author and audience. It matters not that the researcher understand the statistics that have produced the number, merely that they understand enough to produce a conducive result and enough to interpret it, i.e. to know that low=good.

Which leads us to the rigour of rhetoric: producing a statistic out of a set of data naturally involves reinterpreting and recoding data so that a meaningful (as in both making sense and supporting the research questions) result emerges. Start with a conclusion and work from there by altering the meaning of your instruments until you hit something. In a sense, this is merely a description of hypothesis testing, but in the social sciences it's obviously not that simple...