To spam this list as well as Twitter :-)

http://magnusmanske.de/wordpress/?p=250

On Tue, Jan 13, 2015 at 5:41 PM, Maximilian Klein <[email protected]> wrote:

> Thank you all for the feedback. I will have taken away quite a few good
> ideas for further investigation, to summarize:
>
> Gerard - look at the ratios of those bios of a language, which exist only
> in that language.
> Han Teng - "male gaze" hypothesis, create a by-profession crosstabular
> analysis.
> Jane - look at the ratios of leading actors by language, and "fictional
> humans" more closely.
> Jonathan - perform a filter step, or perhaps a weighting by page-views.
>
> Thanks so much for the advice, what a great list.
>
> Make a great day,
> Max Klein ‽ http://notconfusing.com/
>
> On Mon, Jan 12, 2015 at 5:57 AM, WereSpielChequers <
> [email protected]> wrote:
>
>> I have spent quite a bit of time at new page patrol over the years. My
>> suspicion is that many if not most of the people who create articles on
>> newly signed pop stars and actors are from their management agency rather
>> than fans, especially if they seem too early in their career to have fans.
>> Sportspeople I suggest are more likely to be written about by fans,
>> especially if they have been signed by a major team, or more importantly
>> for Wikipedia a team with an actively editing fan.
>>
>> On this theory the quality of articles, the number of edits, and when we
>> had the Article Feedback Tool the number of "is hot" type comments would be
>> a good indication of interest from the volunteer editing community. But
>> article creation is in part a matter of the policy of the relevant talent
>> agencies.
>>
>> Sorry if that sounds overly cynical, perhaps if it were possible one
>> would filter out the articles that get scarcely any views and then look at
>> the gender balance of articles that are of interest to our audience as well
>> as our editors.
>>
>> Regards
>>
>> Jonathan Cardy
>>
>>
>> On 11 Jan 2015, at 22:23, h <[email protected]> wrote:
>>
>> 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%E5%93%A1
>> (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%E5%91%98
>>
>> (2a) Female Japanese AV (i.e. porn) actresses
>>
>> http://zh.wikipedia.org/w/index.php?title=Category:%E6%97%A5%E6%9C%ACAV%E5%A5%B3%E5%84%AA
>> (2b) Male Japanese AV (i.e. porn) actresses
>>
>> http://zh.wikipedia.org/w/index.php?title=Category:%E6%97%A5%E6%9C%ACAV%E7%94%B7%E5%84%AA
>>
>>     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 <[email protected]>:
>>
>>> 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 <[email protected]> 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
>>>>
>>>>
>>>> _______________________________________________
>>>> Wiki-research-l mailing list
>>>> [email protected]
>>>> https://lists.wikimedia.org/mailman/listinfo/wiki-research-l
>>>>
>>>
>>>
>>> _______________________________________________
>>> Wiki-research-l mailing list
>>> [email protected]
>>> https://lists.wikimedia.org/mailman/listinfo/wiki-research-l
>>>
>>>
>> _______________________________________________
>> Wiki-research-l mailing list
>> [email protected]
>> https://lists.wikimedia.org/mailman/listinfo/wiki-research-l
>>
>>
>> _______________________________________________
>> Wiki-research-l mailing list
>> [email protected]
>> https://lists.wikimedia.org/mailman/listinfo/wiki-research-l
>>
>>
>
> _______________________________________________
> Wiki-research-l mailing list
> [email protected]
> https://lists.wikimedia.org/mailman/listinfo/wiki-research-l
>
>
_______________________________________________
Wiki-research-l mailing list
[email protected]
https://lists.wikimedia.org/mailman/listinfo/wiki-research-l

Reply via email to