From: tbn@UTXVM.CC.UTEXAS.EDU ((Tor Neilands))
Newsgroups: bit.listserv.psycgrad
Subject: gender imbalance in psychology--discussion
Date: 5 Nov 92 20:14:09 GMT
              <PSYCGRAD@UOTTAWA.BITNET>
Comments: Gated by NETNEWS@AUVM.AMERICAN.EDU

All of the recent discussion of gender equality (or inequality) in
psychology raises a question that I've heard raised before, and I think it
could be an interesting topic of discussion. Many psychologists would agree
that we (i.e., human beings) have an innate mechanism which drives us to
break our world down into distinct categories (though interestingly enough,
what separates actual categories has been one of the hardest nuts
psychology has tried to crack in recent years--finding universal
categorization laws has been really difficult, though I'm sure the
cognitive psychologists on the net could speak to this issue more
effectively than I).

If we in fact do categorize and categorization helps us to mentally manage
our busy, hetic lives in a busy and hectic world, then the question
becomes: Can we ever see men and women as being truly equal? Should
everyone be exactly the same as everyone else? I'm not so sure that
homogenization is the answer to this issue. I'd be more in favor of
diversity, myself. I know that's really easy for me to say, as a caucasian
male, but I believe that I'd rather be in a department where the females
value their differences from the males--I feel I can learn more about women
from these types of women than I can from women who adopt a more
"male-oriented" approach to psychology. And I'd want to be in a department
with as many different types of folks as possible and feel able to talk to
them about their different life experiences, both in general as members of
minority/gender groups that are different than mine. Conversely, I'd
absolutely hate to be in a department where everyone was trying to be the
same type of person doing the same type of research. I think that kind of
place would be incredibly boring.

I think it really comes down to an issue of value and respect vs. gender
(or race or political affiliation or __________ (fill in the blank with
your favorite type/category of person you think you understand the least)).
I can see a woman come into our department who studies close relationships
and someone (usually an older, tenured, male faculty member) scorn her
because what she studies "isn't hard science" or make remarks that "she's
given up her dedication to science by having a baby" **or** someone can
tell her, "I think it's great you had a baby and that you study topic
X--your perspectives on both of those areas are things I can really learn
from" (especially the baby part--as a male, I can't get pregnant, but I
wonder what the experience is like). I think we sometimes can orthogonalize
value and respect vs. category attributes like gender and race, but it's
hard for us to do, not only because of past socialization, but also because
it's really difficult to understand the thoughts and values and dreams and
goals of someone whom one sees as being very different from oneself.
However, I think if we really try, we can value and appreciate our
differences as well as our similarities, as long as the underlying value
and respect is there. Unfortunately, of course, as we all know, that's not
always the case.

Any thoughts, fellow psycgradders?

take it easy,

Tor


Tor Neilands
Systems Analyst
Statistical Services Group
Computation Center
University of Texas at Austin
Austin, TX  78712

Phone: (512)-471-3241, Ext. 263

Internet:  TBN@Utxvm.cc.utexas.edu
___________________________________________________

"Life is too short to self-verify"   --- Shawn McNulty

"Two roads diverged in a yellow wood and I, I took
 the road less traveled by, and that has made all the
 difference".                                 --- Robert Frost
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Disclaimer:  All of the views expressed above are soley
those of the author. Any relationship between my own
views and those of the University of Texas and/or The
Computation Center at the University of Texas are
due merely to regression to the mean.
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