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Always reblog

As a former zookeeper we would hear this a lot. “If you don’t study hard you’ll end up cleaning poop for a living.” It’s the one time we’re allowed to go off on the visitors. I once heard my boss rant for five minutes at a lady, in front of her kids, about how he had a Master’s degree, how people literally worked there for free, and how dare she judge people without bothering to know anything about them. Later that day his boss came by and said, roughly, “She told us what happened. Thanks for not throwing anything this time.”

I can count on one hand the amount of times I have gone off on people, but employment snobbery gives me the rage. I was showing the new kid how to use the fry scoop at McDonald’s “.. like this, and then just sort of hold it perpendicular and give it one tap..”

And the new kid sniggered “isn’t perpendicular a bit of a big word for McDonald’s?”

Something in me was just so annoyed by this 16yr old who was learning to work right next to me and somehow felt above us? Fuck that shit. I pointed at the people just on the floor and went off, “she’s a 4th year law student, she’s the primary career for her terminally ill daughter, he raises 100,000 for charity every year, she manages 3 stores and more than £16mil in turnover a year. What the fuck do you do?”

He just sort of mumbled “I didn’t know”

“you shouldn’t have to know, you’re not better than us. So. You tap it once and then move it here to release…”

“I didn’t know.”

“You shouldn’t have to know,”

yes to all this because workers can be educated and intelligent, but also, even if workers are formally uneducated or dont know big words that doesnt mean they arent equally deserving of respect

Zookeepers bust their asses shoveling shit and feeding apex predators so you can stare at an elephant without flying to Asia or Africa.

Fast food workers bust their asses surrounded by hot ovens and boiling oil so you can get food quickly without having to make it yourself or even learn how.

Janitors bust their asses cleaning up the most vile things humans can do to a public room so you don’t have to tiptoe around human waste everywhere you go.

Mail carriers bust their asses going door to door in near-fatal heat/cold and have to deal with the possibility of getting attacked by your poorly-trained pets so you don’t have to drive to the post office every single day.

Warehouse workers bust their asses making sure YOUR latest Amazon crap doesn’t just disappear into thin air.

And retail workers bust their asses coddling and picking up after you like your parents because none of you know how to read a price tag or stop deliberately miss-shelving things you never wanted.

But sure, go ahead and act like you wouldn’t be dead in a week without these people.

Predicting Financial Crime: Augmenting the Predictive Policing Arsenal

In this paper we have presented our state-of-the-art model for predicting financial crime. By incorporating public data sources with a random forest classifier, we are able to achieve 90.12% predictive accuracy. We are confident that our model matches or exceeds industry standards for predictive policing tools.

Crucially, our model only provides an estimate of white collar crimes for a particular region. It does not go so far as to identify which individuals within a particular region are likely to commit the financial crime. That is, all entities within high risk zones are treated as uniformly suspicious.

Recently researchers have demonstrated the effectiveness of applying machine learning techniques to facial features to quantify the "criminality" of an individual.

We therefore plan to augment our model with facial analysis and psychometrics to identify potential financial crime at the individual level. As a proof of concept, we have downloaded the pictures of 7000 corporate executives whose LinkedIn profiles suggest they work for financial organizations, and then averaged their faces to produce generalized white collar criminal subjects unique to each high risk zone. Future efforts will allow us to predict white collar criminality through real-time facial analysis.

Previously, previously, previously, previously, previously, previously, previously, previously.

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I just worry kids will never know the pleasure of convincing your exhausted mother that you'll shut up in exchange for the king size candy bar and 6 pounds of Ninja Turtles episodes.