Diversity Club: Third Culture Kids

Hello All,

At diversity club this week a month or so ago, we are going to learn about Third Culture Kids, and you can read about what this is in the short article linked here:

As supplementary material, here is an infographic and a recent nytimes article:
INFOGRAPHIC: The Modern Third Culture Kid

–Abie and Nina

(I remind you that you can bring your own lunch if you would like to eat while we meet.)

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To read: On the plausibility of socioeconomic mortality estimates derived from linked data


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Diversity Club: data, algorithms and prejudice

Was it already a month ago that our Diversity Club discussion was on data, algorithms and prejudice?

For a short introduction to the topic, see this piece from the New York Times: https://www.nytimes.com/2015/07/10/upshot/when-algorithms-discriminate.html?_r=0

For a more in-depth discussion of this issue – specifically, as it relates to workplace equality – here’s an interesting piece from The Guardian: https://www.theguardian.com/technology/2016/aug/03/algorithm-racist-human-employers-work

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To read: Tuberculosis and HIV are the leading causes of adult death in northwest Ethiopia


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Diversity Club: lookism

At last diversity club we most recently we discussed “lookism”, the way that physical attractiveness can drive bias. We have found a short article about provocative scientific controversy to help spark discussion: https://blogs.scientificamerican.com/guest-blog/the-data-are-in-regarding-satoshi-kanazawa/

For an overview and introduction to lookism, also see this article: http://curvylife.com/plainness_penalty/

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Sudoku and Noun Project Mashup in Python

I’ve developed some new airplane material for my puzzle kid: a mashup of my old sudoku generator and my noun project icons in matplotlib code snippet.

It could stand some more refactoring, anyone up for that? Code here: https://gist.github.com/aflaxman/188367eba6d25a4ec41af1a4f468efed

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Dataviz in Python: Stephen Few’s new jittering

I am always excited to get news of a new Visual Business Intelligence Newsletter in my Inbox, and that is what arrived at the end of last week. This time Few takes on “jittering”, and suggests an interesting alternative to adding random noise.

Here is a little python snippet to do it:

def wheat_plot(x):
    hist, bin_edges = np.histogram(x)
    # make y position based on values of hist
    y = []
    for h_i in hist:
        y += range(h_i)

    plt.plot(sorted(x), y, 'o')

Here is a notebook that makes that code do something: https://gist.github.com/aflaxman/235f94f9563b1675233d6d35cd30b8c2

Also Jeff Heer and company made an interactive version in Vega: https://vega.github.io/vega/examples/wheat-plot/

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