Sorry if it was ambiguous, but my use of the term “defend” was meant as a request for the presentation of some supporting evidence (even anecdotal).

Accounting has this same problem; accounts are falling over themselves to give things the lowest possible value. This is best summed up in their favorite phrase, “lower of cost or market.” Understating assets is just as misleading as overstating them, so why do they do it?

Because the pressure in accounting is to overstate. Being conservative has two advantages; primarily it shows you’re not overstating (adding credibility to the numbers presented), and second, it helps compensate for whatever overstating there is.

In science the pressure is to make new ground breaking discoveries. Doubting distinguishes one from those who eagerly jump on every new topic and preserve one’s credibility for when a real discovery is made.

If the pattern were not that many more discoveries were claimed than were made doubting would be a bad, but because most claims are false doubting holds value.

OK, let me take a stab at this: “If A and B are correlated, then either (1) A causes B, (2) B causes A, (3) C causes both A and B, (4) the correlation between A and B is due to random noise and will go away when more data are collected, or (5) A and B are part of a system with feedback loops, and it is not meaningful to ask whether A causes B or B causes A — they cause each other.”

Academics live to show they are not “simple” like ordinary people, but instead apply complex theories and data analysis techniques. So academics tend to reject the simple data and simple theories that persuade most people.

Perhaps the academics are right: There are no simple answers. Consider causality and correlation, for example.

Some examples:

(a) Lack of correlation does not imply lack of causation.

(b) Correlation implies either causation or common cause.

(c) No causes in — no causes out.

James, I still defend my statement.

Based on your comments it does not seem that Robin’s attempted paraphrase is reasonable. “Negative critiques are the norm” is a far cry from “academics tend to reject the simple data and simple theories that persuade most people”. Is there anyone here who actually wants to defend the latter statement?

Closer to home, I’ve had to tell journalists who were inclined to be cautious about the existence of these so-called “superpositions” and “wave functions” that no, they should not be so cautious.

I would not restrict that to scientists. I recall an undergraduate philosophy class where the professor opened discussion with instructions to start with what was good about the author, what we could use, rather than critique. Silence rang out, and it took several minutes for anyone to start getting comfortable with the concept.

Reference online discussions, where “I agree” is usually considered annoying spam rather than useful feedback. You must have something to add, which usually means a point of disagreement.

There is a good answer to this question. See the books of Glymour, Pearl, Spirtes, Scheines, etc.:

http://www.bayesnets.com/CausalityReferences.htm

Unfortunately, I don’t know how to reduce it to a simple saying.

1. Everyone’s heard “correlation does not imply causation”. I’ve never heard a parallel saying about what correlation does imply. Such a saying is possible; it would be along the lines of “something is better than nothing.”

2. Recently I attended a research group meeting in which a postdoc talked about new data she had gathered. The entire discussion was about the problems with it — what she couldn’t infer from it. There could have been a long discussion about how it added to what we already know, but there wasn’t a word about this.

I’m not saying criticism or skepticism is bad; I’m saying that, when scientists encounter new facts, highly unbalanced critiques (much more negative than positive) are the norm. The lack of exploration of what you can learn from new data is the problem — or the opportunity.