[Semi OT] The programming language wars

[via Digitalmars-d]

On Sunday, 22 March 2015 at 10:24:16 UTC, FG wrote:
> On 2015-03-22 at 11:03, "Ola Fosheim =?UTF-8?B?R3LDuHN0YWQi?= 
> <ola.fosheim.grostad+dlang at gmail.com>" wrote:
>> On Sunday, 22 March 2015 at 09:30:38 UTC, Atila Neves wrote:
>>> Of course there is. Experience and judgement aren't 
>>> measurable. You don't have science without numbers.
>>
>> WTF?
>
> Heh, everything is measurable, but sometimes the chosen metrics 
> and analysis are just ridiculous and not worth the paper they 
> are printed on, even though all rules of scientific reasoning 
> were followed. :)

Almost right. Even a well conducted quantitative study might be 
misleading because it measures correlation and not causality. 
Causality is hard nut to crack and it will in the end hang on our 
beliefs in the methodology, the study, the tools, the objects 
being studied, the people conducting the studies and the "already 
accepted assumptions in the field" (established theories which 
might be wrong) etc. So in essence, science is a belief system 
(not all that different from religion, although the contrary is 
often claimed).

This all becomes easier to reason about if people give up the 
idea that science represents "the truth". It does not, it 
presents models that are hypothetical in nature. These may be 
useful or not useful, but are usually incomplete and somewhat 
incorrect... In medical sciences correlation based models can be 
very useful, or very harmful (when incomplete on critical 
parameters such as negative effects of radiation).

In the design field the theories used are applied to a future 
unknown setting so correlation has very low value and insight in 
causality has a very high value. Meaning: a somewhat flawed high 
level model about how human beings think and react, about 
causality, might lead to better design than a more limited and 
correct low level model of how the brain works based on 
correlation.

Whether "everything is measurable" depends on what you mean. You 
might say that qualitative studies involves measuring because 
everything you perceive are measurements. In the real world, the 
data (what you have collected) will usually be inadequate for 
what is being "claimed". After all, it is a society of "publish 
or perish". So you need many independent studies to get something 
solid, but how many fields can produce that? Only the big ones, 
right?