I think everyone’s idea is good.
You can tackle these problems from a “big
data” perspective as Joseph is proposing which has the disadvantage of
being possibly imprecise in its assessment of gender but can potentially scan
the whole of Wikipedia providing a massive dataset. And you can look at “small
data” like existing lists as others are suggesting; with this approach,
the assessment of gender will be more accurate but the sample size will be
quite small (inviting the question whether a larger sample would reveal
something different). There is a lot of benefit of doing both. Big data (a highly
quantitative approach) is good at testing for unusual patterns in the data but not
so good in explaining them; doing a more qualitative approach with small data
analysis is likely to yield explanations. If small data yields a theory on the
more precise characterisation of a pattern, then the theory can be tested on
the big data to see if appears to hold more widely. The two approaches
complement and reinforce one another. Neither approach is better or worse than the
other, simply different tools used in research. Studying small samples requires
skills that most researchers have, which is why it tends to be more popular. Big
data approaches need firstly a large dataset (and Wikipedia is a very large
dataset!) and secondly a strong IT skill set to work with that data, which
limits the number of researchers who can undertake that kind of investigation.
If Joseph has the skills to tackle a big data investigation, I hope he will
tackle it. I look forward to hearing the results from any investigation.
Kerry
From:
gendergap-bounces@lists.wikimedia.org
[mailto:gendergap-bounces@lists.wikimedia.org] On Behalf Of J Hayes
Sent: Tuesday, 14 April 2015 5:56
AM
To: Addressing gender equity and
exploring ways to increase the participationof women within Wikimedia projects.
Subject: Re: [Gendergap] Article:
Wikipedia trolls now vs. women architects
i also collected some anecdotal data about deletions and speedy
deletions of MacArthur Fellows.
you could study differential deletions of them or Fellows of the Royal
Society.
On Mon, Apr 13, 2015 at 2:44 PM, Samuel Klein <meta.sj@gmail.com>
wrote:
Emilio - thanks for the reminder of that excellent page!
On Mon, Apr 13, 2015 at 1:18 PM, Jane Darnell <jane023@gmail.com>
wrote:
I have a theory that it is much more difficult to create bios of females in whatever category due to the systemic academic bias aginst including women's biographies in the list of "reliable sources" mostly used in Wikipedia. I would be especially interested in comparison of male-female ration of bios in established dictionaries of biography and how these compare to Wikipedia, and of those, how many such bios were previously deleted on Wikipedia and recreated.
Agreed. I think one of the most effective ways to counter this
sort of systemic bias is to find dictionaries of biography & encyclopedic
histories of women and digitize them / make them available to editors. Those
sources often do exist, though they are less commonly known or available online.
We have a decent reason for them to relicense those works, especially if we can
more actively help with the digitization as a result.
It would be a small but precise blow against systemic bias to say
"the following areas have historical & reporting bias; so we make
extra effort to find and recognize additional sources, and vary criteria in
inverse proportion to that bias".
Sam
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