Thom,
This is a reasonable question to ask.
Thom:
In the original thread, I referred to
the utility function relating citations to quality, etc,
and I'm aware of numerous difficult issues regarding
the evaluation of this information. My comments, as
I indicated, were addressed primarily to the specific
insistence on the part of Gallagher and Ulrich that
a randomization (or t) test would add useful information.
One can advance all kinds of arguments
about the true nature of the relationship between
citation counts and quality, etc. These questions
can be logically separated from questions about a
randomization test.
I'm quite confident that, if you examine any
data you want, you'll emerge with the conclusion
that a 4.5 to 1 ratio is, in fact, "huge." If you
feel otherwise, do the study and refute us.
An even more interesting question (than
the "hugeness" of the 4.5 to 1 ratio) would be this:
If you go into numerous departments and cull out
comparable groups composed only of men, with 4.5 to 1 citation
ratios, what kind of salary differences do you
observe? In other words, in the world at large,
what kind of salary differences do you tend to
observe between comparable groups of scientists
with 4.5 to 1 citation ratios?
Keep in mind that, in producing the IWF report,
we did not print all data available to us, nor
did we go into as fine a detail as we might
want. The report was aimed at the general public.
We wanted to keep it comprehensible.
However, for most people I know, the notion that a 4.5 to
1 ratio of citations or 2 to 1 edge in publications
is "huge" is about as commonsense as the notion that a 1.7
to 1 ratio of home runs is huge. I felt comfortable with
such a verbal description, and I suspect that, had the
difference been in the opposite direction, Dean Birgeneau
would have felt comfortable publicizing it.
You sound like someone who is fully prepared to have
gender discrimination issues be "performance based."
Most people are not. The fact is, the 9 signatories at the recent MIT
meeting on "gender discrimination" signed an agreement that mentions
absolutely nothing about the use of performance data
to evaluate whether or not discrimination exists.
There is a substantial amount of data that demonstrate
that men have been the victims of discriminatory hiring
policies for more than 15 years in many areas of academics
in North America. Much of this unfair discrimination has been
supported by feminists and "equity officers" with statistical
arguments so obviously flawed as to be quickly refutable by any well
trained 3rd year undergraduate.
For example, one frequently hears discussions [even
within the MIT report] referencing allegations of
"discrimination" to hiring rates, while making no
reference whatsoever to the application rates
in these fields.
This raises an interesting sociopolitical question:
Why is it, do you think, that an allegation that
a 4.5 to 1 citation ratio, over 12 years, between
two comparable groups of senior scientists is
"huge" draws criticism, when the horribly flawed arguments about
"gender discrimination," presented over and over by feminists, seldom
seem to attract criticism? Now that is a really interesting
question.
Jim Steiger
--------------
James H. Steiger, Professor
Dept. of Psychology
University of British Columbia
Vancouver, B.C., V6T 1Z4
-------------
Note: I urge all members of this list to read
the following and inform themselves carefully
of the truth about the MIT Report on the Status
of Women Faculty.
Patricia Hausman and James Steiger Article,
"Confession Without Guilt?" :
http://www.iwf.org/news/mitfinal.pdf
Judith Kleinfeld's Article Critiquing the MIT Report:
http://www.uaf.edu/northern/mitstudy/#note9back
Original MIT Report on the Status of Women Faculty:
http://mindit.netmind.com/proxy/http://web.mit.edu/fnl/
On Mon, 12 Mar 2001 17:13:53 +0000, Thom Baguley
<[EMAIL PROTECTED]> wrote:
>Radford Neal wrote:
>> Yes indeed. And the context in this case is the question of whether
>> or not the difference in performance provides an alternative
>> explanation for why the men were paid more (one supposes, no actual
>> salary data has been released).
>
>I disagree. The original context was that. The baseball example was in
>relation a more general question, else why was it introduced?. (The thread
>header changed, for example).
>
>If you want to say there is a difference. Fine. No dispute.
>
>If you wish to infer that difference is "huge" that requires more than an
>observation of a difference - you need to explain and support that inference
>in some way. My point was that the baseball case allows you to state a
>difference, but an inference about the size of the difference requires further
>support. In the baseball case that support comes almost entirely from
>knowledge of baseball. (Was I really _that_ unclear?).
>
>> In this context, all that matters is that there is a difference. As
>> explained in many previous posts by myself and others, it is NOT
>> appropriate in this context to do a significance test, and ignore the
>> difference if you can't reject the null hypothesis of no difference in
>> the populations from which these people were drawn (whatever one might
>> think those populations are).
>
>Only if the the entire content of the claim is that 1) there is a difference,
>2) that difference might possibly explain something else.
>
>Once you extend the claim to say there is, for example, a "huge" effect. Also
>if you entertain other hypotheses (or allow others to) the situation might change.
>
>Thom
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