5 ms·

I **ing hate clickbait. You say you hate science, but then you go on to state the opposite, that you actually hate stuff being unscientific, not verifying, not

by foxes 5y ago

I **ing hate clickbait. You say you hate science, but then you go on to state the opposite, that you actually hate stuff being unscientific, not verifying, not checking the facts etc. Great.

hugh-avherald 5y ago
No, you're using the normative definition of science whereas he's using the descriptive.
tempodox 5y ago
There are two definitions of “science”: The abstract ideal (roughly, doubt everything until you have reproducible proof), and the way it's put into practice (or not) by institutions, companies, and individuals. The failure modes are numerous, including perverse incentives to do the wrong thing, culminating in outright fraud. See the other discussion here on medical research [1]. It's easy to hate the latter if you value the former. [1]: https://news.ycombinator.com/item?id=27884233 https://news.ycombinator.com/item?id=27884233
cortexio 5y ago
You're missing the point, his point is that alot of science is unscientific. He explains that the main problem is that either the study is full of gaps, aka. unanswered questions. Or either it's a good study, but then continue to make conclusions about an entire subject while their data only represents a part of the subject. And this happens all the time, over and over again. It happens at google, IBM or any other research company. Science is hard! and the people working at these companies are just people like any other people. People like to rush things or claim that they have proven something.. because.. fame, money, recognition, etc etc..
rchaud 5y ago
The title is quite clearly a reference to fluff websites and social media pages called 'I F___ love Science'. Those pages post low-quality blog articles summarizing scientific developments, but don't link to the original research papers. The coverage is significantly juiced up, and readers will take the articles as fact, as they have no reason to believe otherwise. The author's example of a highly-cited IBM chart that can't be properly sourced plays on the same principle as the IFLS sites.

by foxes 5y ago

I **ing hate clickbait. You say you hate science, but then you go on to state the opposite, that you actually hate stuff being unscientific, not verifying, not checking the facts etc. Great.

hugh-avherald 5y ago

No, you're using the normative definition of science whereas he's using the descriptive.

tempodox 5y ago

There are two definitions of “science”: The abstract ideal (roughly, doubt everything until you have reproducible proof), and the way it's put into practice (or not) by institutions, companies, and individuals. The failure modes are numerous, including perverse incentives to do the wrong thing, culminating in outright fraud. See the other discussion here on medical research [1]. It's easy to hate the latter if you value the former. [1]: https://news.ycombinator.com/item?id=27884233 https://news.ycombinator.com/item?id=27884233

cortexio 5y ago

You're missing the point, his point is that alot of science is unscientific. He explains that the main problem is that either the study is full of gaps, aka. unanswered questions. Or either it's a good study, but then continue to make conclusions about an entire subject while their data only represents a part of the subject. And this happens all the time, over and over again. It happens at google, IBM or any other research company. Science is hard! and the people working at these companies are just people like any other people. People like to rush things or claim that they have proven something.. because.. fame, money, recognition, etc etc..

rchaud 5y ago

The title is quite clearly a reference to fluff websites and social media pages called 'I F___ love Science'. Those pages post low-quality blog articles summarizing scientific developments, but don't link to the original research papers. The coverage is significantly juiced up, and readers will take the articles as fact, as they have no reason to believe otherwise. The author's example of a highly-cited IBM chart that can't be properly sourced plays on the same principle as the IFLS sites.