[Air-l] Technical competence

[Ellis Godard]

Just because some folks are applying advanced techniques to data,
doesn't mean that anyone (much less everyone) else needs to understand
those techniques. Frequently, methods employed in the social sciences
surpass the theoretical maturity available. Perhaps I'm archaic to think
that techniques should test ideas, rather than generate them. But even
factor analysis and stepwise regression give me pause - not because I
lack the technical competence, but because sampling deviations may
generate findings that won't hold beyond the available sample.

-eg

> -----Original Message-----
> From: air-l-aoir.org-bounces at listserv.aoir.org 
> [mailto:air-l-aoir.org-bounces at listserv.aoir.org] On Behalf Of Cox
> Sent: Tuesday, June 07, 2005 4:23 AM
> To: air-l at listserv.aoir.org
> Subject: RE: [Air-l] Technical competence
> 
> 
> The need for knowing about computer technologies in 
> communications research is becoming greater than the 
> rudiments of web composition and traffic analysis. Already, 
> artificial intelligence is being applied to content analysis, 
> as in the case of a number of papers published on the Enron 
> email corpus. The skill sets involved fall outside those 
> typically found among communications researchers. A principle 
> researcher in one of these Enron studies is Andrew McCallum 
> at UMass, who is a physicist iirc. Another physicist, Andrew 
> Smith, is responsible for the Leximancer tool mentioned 
> earlier by Thomas Koenig. Less abstract tools like structural 
> equation modeling are common now, and require competence in 
> computer technologies beyond SPSS. 
> 
> Whether these technologies should be incorporated in 
> curricula is maybe not the right question, as they are not 
> the types of skills one gets in a course or two. Perhaps the 
> field should recruit from among information science and 
> computer science undergrads who come equipped with the skills 
> already.