Quote from: bitcoinbitcoin113 on March 08, 2013, 11:18:09 PM

Quote from: nanopene on March 08, 2013, 11:09:18 PM

Quote from: bitcoinbitcoin113 on March 08, 2013, 10:34:20 PM

Quote from: nanopene on March 08, 2013, 09:42:27 PM

First of all we must define that science is the pursuit of objetive understanding of the natural world, first and utmost.
Then IF this understanding is true, it should be testable, reproducible, therefore, it should have predictive power.
And IF this understanding is false, it should be provable as false.
This is the key requirement to be scientific.
Science+Time refine this knowledge. High accuracy is not an excluding requirement to be scientific (or to discredited), but it is a refinement of the result of this testing and retesting process over time to confirm, improve or reject an hypothesis or a theory. It is really not the result but the process that matters.

Yes, please show me a paper from any of the fields you listed that falsifies a real prediction. As I said, as practiced, the things getting falsified are worthless because we know them to be false before trying to falsify them. It would be the same as if TA was deemed accurate because it predicted the price would not be exactly the same tomorrow at this second as it is now. So it is just a 50-50 chance of guessing right up or down.

That is a grave statement and a deep misunderstanding of the scientific process.
First of all, what is your profession? I just want to know what kind of audience I am responding to.
Are you a graduate student in hard sciences, an academician or just an average joe fanatic of the sciences?
If you are one of the first, I am appalled at the lack of epistemological understanding. (this is something I also realized among the grad students in my school)

You can never know what is false unless it is tested. If your mentality was widespread, all counterintuitive hypotheses would be rejected from the get go. That kind of prejudgement is very harming for scientific discoveries, which makes me think that you are not actually related with any scientific discipline, either that or you are too new to this.

If you want to know about researches in social sciences, simply subscribe to social scientific journals yourself. If you work in academia, you should have free access to all of them. You have plenty of social disciplines that use quantitative research.

You are severely misunderstanding me. Take any two groups of people and compare them along any measure and you will find they are different if you look close enough. I "know" this as much as I can know anything. This is what occurs in the social sciences. Here is a good description of the problem from back in 1967:

http://www.psych.ucsb.edu/~janusonis/meehl1967.pdf

Funny, I needed this paper to troll my professors

To be honest, I have my own criticisms as well, but I wouldn't go as far as saying that soft sciences are not real science.
It is science, not pseudo, not fringe, it IS science. At least psychology is a field that has been serious about it, and within psychology, neuropsychology, behavioral neuroscience, comparative psychology, neurobiology are the hardest of all in the spectrum of the psychological subdisciplines. In fact, there is nothing really "soft" in them, they all are very well versed on NHST (well, they should be), it is a requirement for research for that line of study.
I will read that paper with more time to dissect it carefully later, I love it, thank you.

Now, responding to your remark: "compare them along any measure and you will find they are different if you look close enough".There are always differences, that's granted. What matters is if it is statistically significant. To be sure there are different experimental designs to filter out, changing criterion, reversal and other that are very well known in medical research, double-blind testing, control groups. We use Analysis of Variance to tackle that problem, which is the same statistical tool used in any other "hard" science.

The only difference with the hard sciences, is that we are much younger and growing.
Btw, we are way offtopic.

PS: Let me share this paper: http://www.statpower.net/Steiger%20Biblio/Steiger04b.pdf