I agree with this article, but think that by singling out social sciences it fails to reveal the bigger picture: that all scientific fields are subject to these same mistakes.
I just started working in a research lab at a hospital that creates finite element cardiac models based on data taken during heart surgeries on sheep along with MRI images taken at various intervals pre and post surgery. Although I'm still new to this position, it seems that our own methods are subject to just as much deception. We basically want our models to coordinate with the actual heartbeat at only two exact moments, during the beginning of contraction and relaxation. If I've understood what's been done before, modeling these two brief periods during a single heart beat are all that are needed for publication.
I bring this up not to criticize my lab, obviously our work is meant to be a progression towards getting more and more accurate models. I just think that it shows that even something that is considered hard science is subject to many of the same faults as anything else. There are so many parameters and considerations to take into account that I don't think the end goal is to build a comprehensive theory that explains computational modeling of physiological function in a similar way to how Newton's laws predict the motions of the planets. The goal is simply to create a model that works for the purposes of helping diagnose and treat people more accurately.
It seems that a crisis is imminent in the coming age of computational, statistical, and mathematical applications to all fields where researchers are not properly taught to distinguish between data science and building actual theories. Just as there is a humungous gap between using a computer and actually coding, there is an equivalent difference between being able to collect & analyse data with a computer, and able to actually build a substantial theory that can describe a vast number of phenomena and result.
Essentially there are two rules here: don't post or upvote crap links, and don't be rude or dumb in comment threads.
It later defines deeply interesting as 'stuff that teaches you about the world.' I would by no means consider this a crap, or superficial article. I likewise believe it adequately fulfills the 'teaches you about the world' statement. Please explain my fallacy.
As the OP, I believe this post is consistent with the hacker news guidelines. As it states in the welcoming:
Essentially there are two rules here: don't post or upvote crap links, and don't be rude or dumb in comment threads.
It later defines deeply interesting as 'stuff that teaches you about the world.' I would by no means consider this a crap, or superficial article. I don't consider your comment necessarily rude or dumb; however, I do consider it misinformed.
The article does not posit the media should be subjective: it is rather objective in stating that the media is failing to state the reality of the situation. Another key example of comparative value is global warming.
The global warming debate taking place in the media is almost universally framed as a democrats vs. republicans, liberal conservative debate. It is not. The politicians getting quoted on mainstream news sources are not the experts qualified to be making statements regarding the human induced global warming debate. They are not actively publishing, and doubtfully reading the scientific literature published in dozens, if not hundreds of journals which nearly unanimously acknowledge that there is a high probability of humans having a noticeable impact on climate change. Yet, the scientists denying human induced global warming nearly all have either direct ties with or strong affiliations of companies and people whose interest is to fight global warming for economic gain.
This article essentially mirrors that same argument except replacing scientists, you may essentially think of the objective viewpoint having to do with constitution and law, not political divides.
http://www.cs.cmu.edu/~rwh/pfpl/2nded.pdf