Okay. The one thing is that these writers are so diverse that it's hard to summarize them all in one post.

But basically, they're all contrarians who question the very models that most people (including academics) follow. Basically, they're all about taking risks, short incremental bursts of productivity, and economics based on non-financial principles of values. Are they right on everything? Who knows. But it's refreshing to see what they say.

E.g. here's one of Venkat's good quotes (I can't take too much) - from http://www.quora.com/What-careers-or-industries-are-the-most-meritocratic/answer/Venkatesh-Rao?srid=0WH :

This question is deeply misguided. "Meritocratic" usually indicates some rigid and static notion of merit, usually based on testing/scales/numbers games in mature and professionalized domains. So highest scores, most papers/patents, things like that. Even "highest customer satisfaction scores" is a meritocracy scale.

Being meritorious in this sense has very low correlation with being effective in most fields. "Merit" is entirely about individual qualities, "effectiveness" is about the quality of an individual in a given setting. Merit is neither necessary, nor sufficient for effectiveness. It is often a major source of ineffectiveness.

The clause "where luck, nepotism, etc. are minimized" shows where the question is going wrong.

Luck is good. Hire people who know how to get lucky. People with good radars, peripheral vision, daring and an opportunistic streak. They are rarely "meritorious" in any measurable way, but are highly effective. The meritorious types hate them, because their influence and rewards can seem disproportionate to their effort. These lucky, opportunistic types are often amateurish bumblers when evaluated purely on various scales of professional "merit."

They may even have NO personal qualities that contribute to their effectiveness: they may just happen to know one useful thing by accident. Would you give up a treasure-hunting expedition simply because the person who has the map is a happy-go-lucky drunk who happened to find it in a dumpster by accident while looking for food? Judge people by what they can do, not who they are. As Forrest Gump told Bubba's family, "stupid is, as stupid does."

http://onthespiral.com/wp-content/uploads/2011/06/Value-Universe21.png (from http://onthespiral.com/unifying-value-universe) basically summarizes one of Greg Rader's main points.

Summarizing quote:

The conception of attention economy presented above unites two definitions that superficially contradict each other. In marketing conversations, attention economy refers to the usage of various tactics that convert attention into sales (represented in the image below by the vertical arrow). In discussions of peer-to-peer social media, attention economy refers to analogous tactics that empower individuals to convert weak ties into strong relationships (represented by the horizontal arrow).

And here is one of Lemire's excellent points (http://www.daniel-lemire.com/blog/archives/2009/09/14/how-things-change-cheaters-are-innovators/):

You do not convince existing journals to give more respect to this new field you created. You go out and create your own journals and conferences. John von Neumann did not wait for his colleagues to approve of his work on Computers. In fact, he had to use threats to get what he wanted.

Another one (http://www.daniel-lemire.com/blog/archives/2007/12/05/formal-definitions-are-less-useful-than-you-think/):

There is a widely held belief that shared formal definitions improve collaboration. Certainly, most scientists share several unambiguous definitions. For example, there cannot be a disagreement as to what 2+2 is.

In crafting a research paper, it is important to keep ambiguities to a minimum. You do not want the reader to keep on wondering what you mean. Yet, many highly useful research papers contain few, if any, formal definitions. In fact, entire fields exist without shared formal definitions. One such fields is OLAP: the craft of multidimensional databases. The term was coined by Codd in 1993, yet, as of 2007, I have no yet seen a formal definition, shared or not, of what OLAP is! But it gets more interesting: even the common terms in the field, such as dimension, are fuzzy. What is a dimension in OLAP depends very much on who is holding the pen. Yet, there is no crisis lurking and people do get along.

In short, you do not need shared formal definitions to be productive as a group. A good research paper does not need to introduce formal definitions. Your research papers will be slightly ambiguous.