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Atipica Obtains $2,000,000 Seed Financing

从 Alkanadi, 2016年10月26日

讯息： 6

语言: English

Alkanadi (显示个人资料) 2016年10月26日上午6:53:53

"Atipica, which means atypical in Esperanto, was founded in 2015 by tech industry veteran and diversity advocate, Laura I. Gómez."
http://www.xconomy.com/san-francisco/2016/10/21/at...

Vestitor (显示个人资料) 2016年10月26日上午10:13:33

The company itself makes software that reduces people to data.

Roch (显示个人资料) 2016年10月28日上午4:07:16

However, it's similar to spanish without accent... (having Gómez in mind)

atípico, atípica
adjetivo
diferente, distinto, infrecuente, singular, anómalo.

edit

No hint about esperanto in her life...

http://money.cnn.com/interactive/technology/15-que...

Roch (显示个人资料) 2016年10月28日下午2:27:13

After a second tought... with "mal"
Typical in esperanto is tipa, so it would probably be maltipa... My best guess.

yyaann (显示个人资料) 2016年10月30日上午1:36:46

Vestitor:The company itself makes software that reduces people to data.
Is that different from what a typical recruiter would do though? As is examplified by this Quora answer here, recruiters tend to decide if a resumé is worthy of attention in a matter of seconds based on general criteria. Only those that pass this criteria-based test will go through a more thorough analysis. Recruiters have to do this because otherwise the number of resumés to read through and through would be unmanageable. In fact when I read Ambra Benjamin's comment on Quora on the pre-selection phase, I thought that a machine-learning algorithm could save her a lot of time. I'm actually not surprised that this is already a thing.
After a second tought... with "mal"
Typical in esperanto is tipa, so it would probably be maltipa... My best guess.
I've seen "netipa" more often though.

Vestitor (显示个人资料) 2016年10月30日上午5:14:02

Every week there are thousands of unsuitable people who are hired after a lengthy, so-called criteria-based selection process. Somehow this only seems to be discovered after they have been formally employed. Perhaps because prospective employees paint a false picture of themselves, for obvious reasons. Why employers appear to fail to see this beforehand is less obvious, to me at least.

There are deeper reasons for hiring someone than the statistical results from collated data.

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