Hello Piotr and Gerard,
I think a competing hypothesis would be "male gaze". That is to say,
the more female representation is not about a culture (defined as national,
ethnic, linguistic or regional, not macho/feminine), but rather a
gender-interest bias. Thus the more female representation could mean more
male dominant culture, which is against the theoretical assumption of
Piotr's research.
Note that East Asian Wikipedians that I know, especially those who edit
Chinese Wikipedia, are predominantly very young. Some of them can be highly
interested in opposite sex.
Check the following category pages as examples:
(1a) Female actresses of every countries in the world
http://zh.wikipedia.org/wiki/Category:%E5%90%84%E5%9C%8B%E5%A5%B3%E6%BC%94%…
(1b) Male actresses of every countries in the world
http://zh.wikipedia.org/wiki/Category:%E5%90%84%E5%9B%BD%E7%94%B7%E6%BC%94%…
(2a) Female Japanese AV (i.e. porn) actresses
http://zh.wikipedia.org/w/index.php?title=Category:%E6%97%A5%E6%9C%ACAV%E5%…
(2b) Male Japanese AV (i.e. porn) actresses
http://zh.wikipedia.org/w/index.php?title=Category:%E6%97%A5%E6%9C%ACAV%E7%…
It is quiet clear that the male gaze hypothesis seems to apply here.
More female presentation simply because they are there to be consumed by
men or boys.
So one of my suggestions for research is to select a few professional
categories that are of interest (say, politicians, poets, entertainers,
etc.) to do some cross-tab analysis.
Thus, I will be extremely cautious against using the current
metrics/methods as viable "gender inequality index".
As a proponent of "data normalization" and "geographic
normalization"
method myself, I would distinguish two sets of comparisons: one is
cross-country or cross-language version absolute value comparison, another
is cross-country or cross-language version "normalized" value comparison.
By geographic normalization, I mean that researchers must gather another
set of cross-country or cross-language datasets that captures some aspects
of realities "external" to Wikipedia. In this case, I would say the
Wikipedia represented politicians' gender ratio against the offline gender
ratio of politicians. In other words, "data normalization" allows
researchers to compare which language version are more or less (and how
much) equal than the corresponding offline societies.
BTW, the methods you develop to extract gender from biography articles
for large-scale analysis may also be re-purpose to study other dimensions.
One dimension that will interest me would be nationality. It will be
interesting to see the coverage, focus or bias of a language version on
people based on nationalities. Age might be another one.
Best,
han-teng liao
2015-01-11 19:01 GMT+02:00 Gerard Meijssen <gerard.meijssen(a)gmail.com>om>:
Hoi,
Having read it, I find it is still very much a Wikipedia oriented.It makes
use of the toolset by Markus. That is fine. the notion of diversity and
notability is also very much culturally defined. It would be nice to know
how the different wikipedias accept notability of people from other
cultures and if it impacts the diversity of their own articles.
I have found that many people do not have an article in the languages of
their own cultures. Often it has to do with an interest in a domain that is
more of relevance to the other culture.
Diversity is very much part of a domain; in Roman Catholicism male
dominance is obvious. I am curious if diversity in gender is affected by
such considerations and if items with a single article are more in line
with what is the norm for a culture, a domain.
Thanks,
GerardM
On 10 January 2015 at 11:51, Piotr Konieczny <piokon(a)post.pl> wrote:
Here
(
http://notconfusing.com/preliminary-results-from-wigi-
the-wikipedia-gender-inequality-index/) are some early findings from a
research project I am involved in (together with Maximilian Klein). (To
find out more about the project, see
https://meta.wikimedia.org/
wiki/Research:Wikipedia_Gender_Inequality_Index and it's talk page). We
are very curious what you think (don't hesitate to be critical). What we
would really appreciate would be any alternative hypotheses (to the one
presented) that could try to explain why post-1950s Confucian and South
Asian clusters seem so much more inclusive of female biographies than
others (including the "Western" clusters). Are we seeing a data error, or
something else - and if so, what?
--
Piotr Konieczny, PhD
http://hanyang.academia.edu/PiotrKonieczny
http://scholar.google.com/citations?user=gdV8_AEAAAAJ
http://en.wikipedia.org/wiki/User:Piotrus
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