Gerard,
Actually historically speaking, there will be fewer Harvard alumni as
women because they graduated from Radcliffe, not Harvard, no?
Anyway, how about a trade - I will send you all of my male-female data
with Wikipedia entity names, and you send me back the Q numbers? Or
can you only accept data with Q numbers as a field?
Jane
2014-04-21 7:58 GMT+02:00, Gerard Meijssen <gerard.meijssen@gmail.com>:
> Hoi,
> I blogged about the issue of sex ratios on Wikidata [1]. The experiment I
> did with Harvard alumni was to get some idea about the number of humans who
> were not yet known as human. I added a substantial number of them to have
> an item for each entry in the category on the English Wikipedia. I assume
> that as a group they are relatively well covered; they are ivy league and
> some of the best and brightest studied there. When you look at the sex
> ratio for the Harvard educated, you will find that it is worse than for the
> general population. I suppose it is an indication of the amount of items
> that still need to be identified as human.
> Thanks,
> Gerard
>
>
> [1] http://ultimategerardm.blogspot.nl/2014/04/wikidata-its-sex-ratio.html
>
>
> On 21 April 2014 00:53, Stuart A. Yeates <syeates@gmail.com> wrote:
>
>> On Sun, Apr 20, 2014 at 7:11 PM, Gerard Meijssen
>> <gerard.meijssen@gmail.com> wrote:
>> >
>> > To be blunt, Wikidata gains the quantitative quality I am looking for
>> when only male and female
>> > is added where applicable. Transgender issues with respect are edge
>> cases.
>>
>> Transgender issues are primarily raised because they're vitally
>> important for people today, but they're not the only issues.
>>
>> Far more numerically superior are the issues of people writing under
>> other-gendered pseudonyms; that's a systemic problem, in the GND data
>> for example. "Lord Charles Albert" "Florian Wellesley" and "Currer
>> Bell" were only outed as pseudonyms of Charlotte Brontë once she
>> achieved a certain level of fame. Modern analysis suggests that there
>> are probably thousands if not tens of thousands of other writers who
>> never achieved that level of fame and never had their pseudonyms
>> revealed. GND and similar library data commonly base their gender data
>> on nothing more than the apparent gender of the name on the cover page
>> (librarianship practice, unlike archival practise, takes such things
>> at face value). To take that librarianship practise out of context and
>> assert that that those thousands or tens of thousands of authors were
>> men (rather than just publishing under male or ambiguous names) isn't
>> going to get you sued, but that doesn't mean it's not the
>> white-washing of generations of women writers.
>>
>> cheers
>> stuart
>>
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>
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