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Hey, who wants to read a story about @Upwork fucking over freelancers in order to upsell their clients on unnecessary services the clients don't want and can't afford? Strap in!

So after my marketing agency closed I started freelancing again. A marketing company that wanted to work with me only hires freelance writers through @Upwork. So I signed up. I wasn't thrilled about it, but that's who they contract with and it's their marketing company.

I've been receiving regular assignments from this company, thru @Upwork, for over a month now. I've written dozens of articles for them. My work has been exemplary. I've been handling repeated rush jobs and delivering. The client was and is very happy. That's coming from them.

While I was wrapping up several assignments this week I was contacted by the marketing company. They asked if I had taken a new full-time job and wasn't available anymore. It seems @Upwork's talent group told them I was no longer available to take assignments.

I was very surprised. Nothing had changed on my end. I still needed the freelance work very much. I told them so. So the marketing company pressed @Upwork and were told there were "compliance" issues that were preventing the marketing company from giving me any more work.

Today we’re going to talk statistics and semantics. I’m going to do so via the medium of one of Twitter’s favourite stats 1.7% (aka “intersex is as common as red heads.”). The statistic comes from Fausto-Sterling’s work, which you can see a review of

To understand the statistic, we have to drill down into what the meaning of the word intersex is. Most people think of hermaphrodites. Let’s stress at the beginning there has been no example ever of a human being with both sets of working reproductive organs.

There is a very tiny percentage of people who are born with both testicular and ovarian tissue (what Fausto-Sterling calls “true hermaphrodites”). And when I say tiny, we’re talking intersex tiny, as in 0.0117/1,000 live births, or one in 1,000,000. These are very complex cases.

So, how do we arrive at 1.7%? What Fausto-Sterling does is apply a wider scope. Instead, she argues that intersex is anything that doesn’t fit into a platonic ideal. The platonic ideal, in this case, being a phenotypically perfect XX female and a phenotypically perfect XY male.

This means that intersex, used in the context of the 1.7% statistic, includes people for whom there is no sexual ambiguity. Take for example Klinefelter syndrome (XXY males). As Fausto-Sterling acknowledges, many males can go their whole life and not realise they are XXY.

Java was first released in mid-1995, just 6 months before JS.

By 98, when I went to college, Java was already used for all the first level courses in the CS program.

How did it catch on so quickly (just 3 years) to shift university curriculum, which is usually so slow/behind?

I wonder why Java was so respected and JS was not? Why/how was Java already seen as such a stable and mature language?

Not just Java, other languages (like python) were also released around/near 95, and also seemed to get to "mature" respect status. much quicker.

I bring all this up because my impression of Java in 98 was that it had been around "forever" (as had C++ first developed in 79, but not standardized until 98!), but that's not. true at all. These were all new languages around the same time.

I'm sure the language designs had different merits, and the target applications meant a different perception and reception, but...

it sure seems like the industry (and academics) just decided Java and C++ were the stable mature ones and langs like JS were toys.

BTW, before you assume JS was nascent/immature b/c the web wasn't much of a thing yet, remember that JS was actually released as LiveScript on the server before it was released in a browser. So "server-side JS" was always part of the story, not just Node 15 years later in 2009.

For decades, Jeff Bezos shunned ads.

But now, Amazon’s ad business is huge: it’s on a $30B+ annual run rate (more than 2x the combined sales of Twitter, Snap and Pinterest).

Here’s how it happened 🧵

1/ Amazon doesn’t break out its ad business separately in financial filings. However, most analyst believe ads make up the majority of its “Other” revenue segment.

This figure has exploded from $1B in 2015 to a current annual run rate of ~$32B.

2/ In 2009, Bezos said “ads are the price you pay for a crappy product”.

But the business is so lucrative that Amazon’s interface has been swamped with ads:

◻️ First 3-7 search results (left in red)
◻️ Most of the product page (right in blue)

3/ Prior to the rise of ads, Amazon set out to build the ultimate organic customer recommendations engine.

The approach was codified in a famed 2003 research paper: “Amazon Recommendations: Item-to-Item Collaborative Filtering.”

4/ In recent years, Amazon organic recommendations:

◻️"Customers who bought this also bought this"
◻️"Customers who viewed also viewed"

Have been replaced w/ ads:

◻️ "Sponsored products related to"
◻️ "Brands related to this category"

How do you optimise your slides, audio or video when delivering online teaching?

There are many learning theories out there, but Mayer’s Multimedia Learning Theory is epic.

Read this thread + use his theories to improve learning transfer

Non-ideal slide to get started👇

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