Can you share approximately what fraction of the documents got filtered out with your toxicity detection? Also, I wonder what thresholds you used on Detoxify for filtering?
> 3. The education itself, which should be intellectually challenging (more or less depending on subject, with STEM subjects usually moreso, especially at top tier schools)
Your implication that non-STEM fields are less intellectually challenging is pretty insulting. Have you enrolled in a non-STEM degree? Do you have evidence that writing a treatise on comparative literature or archeology is less intellectually challenging than pushing out some code or solving some derivatives? Please choose your words carefully when communicating.
Whilst I agree the wording could have been better, I think the parent has a point.
I did a double-degree in Commerce (Finance and Economics), and Computer Engineering at Sydney Uni.
English is my first language, and I've always liked economics/finance. However, I found the commerce side of things much easier to cruise through (I was working full-time as well). The material was easier, contact hours were much less, you could fluff your way through essays (to a degree), and it was obvious many of the students there (i.e. international students) just wanted to finish, and get their degree (nothing wrong with that in itself). Many people didn't bother showing up, and just studied online, and sat the final exam.
Engineering...oh man. The material was tough, the maths was tricky, and there was many mandatory contact hours or mandatory tutorials (> 20 a week). If you didn't show up to weekly classes, you got marked down, which is basically a fail. And while you can fudge an essay in commerce (assuming some basic grasp of first principles), try fudging an answer on Fourier transforms, or gradient-descents. However, many people genuinely had a passion for the subject, and the lecturers/tutors really did push you hard.
Also - look at the dropouts rates for fields - a lot more people dropped out of engineering degrees by year 2/3 versus say, Commerce. I can't speak to other fields/areas.
This experience may not apply to everybody - but as somebody who did a degree in both fields, I think it's telling.
I'm comfortable making that claim, and yes I had a mixed education of roughly 1/3rd hard STEM (CS, math, stats), 1/3rd soft STEM (Econ, Law), and 1/3rd non-STEM (economic history, philosophy, required undergrad writing elective).
Things like the Sokal Hoax are difficult to impossible in hard STEM fields. Non-STEM fields are more difficult to falsify and thus more difficult to apply similar levels of rigor. Smart and clever undergrads figure out their professors' biases and are constantly submitting lesser versions of the Sokal Hoax for their writing assignments (been there, done that). You can't do that in hard STEM fields, and its more difficult in some logically rigorous soft-STEM ones like law classes. Non-STEM fields tend to be held in the fuzzy-logic-based natural language you grew up with and know intimately, while STEM fields require learning an entirely new language (math, code) where fuzzy logic does not work and precise logic is required. It's more difficult for a variety of reasons.
If you have the aptitude for it, I'd argue that being constrained by clean, cold, infallible logic makes STEM subjects much easier, not harder, than the messy human whirlpool of the humanities and social sciences. Sure, it might be easier to get away with BS in those fields — but what if you actually want to learn something or make a tangible impact? No matter how you slice it, humans live in the world of "fuzzy-logic-based natural language," not bits and bytes. (Incidentally, this might reveal why some engineers struggle with things like UX, technology ethics, or algorithmic bias.)
I also have a mixed education of 1/2 CS and 1/2 Music. I found some of my music classes way harder (and often way more enjoyable) than many of my CS classes, despite the fact that the latter dealt with well-scoped problems.
When I was in college I dropped an almost-finished comp-sci degree to switch to the humanities exactly because it was harder. I was damn bored in those classes studying interrupts and recursion. Arguing about ideas was way more fun (I know in grad school you get to that in comp-sci and other maths, but I was not planning on going there).
You have a point with aptitude making hard logic easier than fuzzy logic for some. But I would observe that such folks are the minority, not the majority, making hard logic more difficult for the population on average.
Am I the only one made uncomfortable by someone asking if 170k is a good salary, and made even more uncomfortable by the people inquiring if that's enough to maintain a decent quality of life? 170k is over 2.5x the median income in Seattle, and people start families and find contentment with far less.
Perhaps a less entitled way of phrasing the question would have been "Is 170k an appropriate salary for a software dev in Seattle?" I think my issue is with the implication that 170k might not be a good salary to maintain high standard of living.
As tech workers with the potential to earn these large sums, we should be aware of our privilege, and cognizant of how the rest of the population lives.
This is a tech forum and not reddit. Most folks here are within the tech industry and I have seen threads where people have been discussing $400k salaries like it is no big deal. So I feel this is a fair way to phrase the question given the forum's context.
Why should anyone feel guilty relative to the median income?
The real guilt should be in not being paid what you are worth for too long.
Seeking greener pastures and getting compensated in line with what you're worth should be celebrated!
OP, shoot for 200k+ and I'd suggest going to Facebook. I'm confident their stock will do wonders in the coming years and they have very interesting problems due to scale.
It's common (if not strictly accurate) for people to think of HN as a programmers' forum, so the OP probably thought "software dev" could be omitted as already in scope. It is mentioned, after all, in the second sentence of the main text.
To prevent misunderstanding, we've inserted "for a software developer" into the title above.
If people create value for an organization shouldn't they capture some of it for themselves? The less a developer is paid, the more the execs/investors are pocketing. That money goes somewhere.
OpenSteetMap is very difficult to compare to Google Maps as it uses pre-rendered raster map images at fixed resolutions, rather than a dynamic vector-based approach. For me at least, this makes it far slower to load in non-cached areas, and the lack of precise zooming is super annoying.
For me Google Maps is slower than OpenStreetMap anywhere in the world, cache or no cache. Might have something to do with not using Chrome, where Google makes their websites work the best of course.
What do you mean by "the lack of precise zooming is super annoying"? In my experience, zooming in Bing Maps and OpenStreetMap are very fast, and only in Google Maps you're waiting ten seconds for the region to load and browser to respond before you can zoom further.
On Google Maps, your zoom factor is any real number within a range. On Open Street View, you are stuck using one of several predefined zoom levels (integers 1-20).
Google maps also changes the zoom level to the nearest integer. You can't do 12.5 for example. When I change the 10 on the google maps link in your comment to 10.5, it rounds it back down to 10 and rewrites the URL. Have ran into the issue before doing custom maps for sites where 14.5 would be the perfect zoom level, but can only pick 14 or 15 :(
There's vector stacks using OpenStreetMap data, I guess it will be a while before one is in use on openstreetmap.org.
Mapbox has one, Mapzen has one, various apps have their own vector map implementations, there are convertors that take OSM data and output maps in the custom vector formats used by GPS devices and so on.
When Apple came to my university to run an engineering recruitment event, they flew in 12 employees to speak with us, zero of which were female. When asked by the audience about the presence of female engineers at Apple, they sputtered some non-sensical reply. If not enough women are applying for engineering jobs at Apple, then at least one of the reasons is that the company is not making sufficient effort to try and recruit them.
