Any existing 2nd-level domain registrant automatically gets assigned a new TLD equivalent to the current 2nd-level name minus the TLD suffix. Collision priority scheme is .edu, then .com, then .org and .net, then .gov, and finally .mil. Ignores ccTLDs.

First, take care of the .edu sites: Automatically register a new TLD for each registered .edu name, such the that new TLD is the 2nd-level part of the existing .edu name. For example, Harvard U. currently owns 'harvard.edu.', so they would automatically receive the new 'harvard.' TLD.

Second, it seems reasonable to assume that the .com names have higher visibility than the .net/.org names, but not quite as over-riding as the grant to the existing .edu holders. Autoregister the new TLD and give it to the .com holder, but allow a weighted bidding process if the current .net or .org holder wants to try to buy the rights: During some designated 6-month period before open TLD registration starts, the .org/.net holder puts a bid of X dolllars in trust, and the .com holder has 60 days to match 20% of X (single-round bid, weighted at 0.2). That weighting is pretty arbitrary--it doesn't really matter what the actual weight is.

Third, whatever's left in the TLD space gets assigned to .gov and .mil names, on the same basis as .edu.

It's not perfect--it totally ignores ccTLDs, and the weighting is arbitrary, and who am I to say that a .com name is more of a claim on the new TLD than a .net/.org name?

But do you think an unqualified, disorganized "land rush" would be somehow better? At least this way, you're limiting the number of trademark/squatting cases that have to be litigated.

Don't know about that. But you could certainly start calling yourself "celibate", at that point.

...and those who can't be bothered to RTFA, while rushing madly to post first, are doomed to look like morons (or trolls, at best).

In the immortal words of Jeff Lebowski, "Obviously, you're not a golfer."

I've seen a lot of Slashdotters mistake humor or irony for a serious post. But you, sir, have distinguished yourself, even amongst that august house.

+1 Futurama!

And yeah, point B isn't actually proven by point A. But we're talking about the neurological and cultural prejudices of Home Sapiens, here, so we're pretty far from what I'd call "logical". As long as "swift-boating" and "borking" are effective political tactics, we really ought to admit that.

Sigh. It's a very common misconception that the term "mother fucker" (two words, not one) denigrates a man who has sex with his own mother. Fuck Wikipedia, and fuck the ignorant idiots who spin whole fictions, and especially fuck the lazy dipshit readers who just assume that WP is correct, because it's easier than following up with their own research. Yeah, you heard me--Jimmy Wales can suck a fattie, while we're at it.

In reality, the term "mother fucker" refers to a man who has sex with SOMEONE ELSE'S MOTHER, specifically with a woman in some kind of tight spot (e.g., economically) who agrees to sex with that man only out of desperation. The woman doesn't really want to sleep with this man, and she isn't a prostitute in the professional sense, but this man presents an alternative to watching her children go hungry.

The term gained tremendous traction during WWII, originally amongst black American GIs, and was applied literally to American soldiers (black, white, or otherwise) in war-torn Europe who would trade food, money, or anything of value (cigarettes, chocolate, booze) for sex with desperately poor or starving French and German women. Many of these women were home-makers whose husbands had been conscripted away, killed, or imprisoned, leaving the women to support the couple's children alone. Many lacked trade skills, and the war damaged the local economies so badly that they had few, if any, alternatives.

So calling a man a "mother fucker" meant that he was A) taking advantage of poor and downtrodden people with no options, and B) incapable of seducing non-desperate women. Anyone with experience growing up in desperate poverty, or who saw his own parents humiliated by circumstances beyond his control, would probably consider that kind of behavior to be a pretty low thing.

In the last sixty or so years, the term has entered the popular slang as a term of derision ("That Richard Nixon is a real mother fucker, you know?"). More recently, it's been used as an indicator of extraordinary intensity, not necessarily in a derisive sense, but usually still carrying some implications of harshness ("I fell asleep out in my lawn chair, yesterday, and got a mother fucker of a sunburn.") or intimidating awesomeness ("That Shaft, he's one baaaad mother fucker.").

Do your part--fight the ignorance!

That's the most retarded thing I've ever heard. So the CEO has the most CRITICAL, SUPER-SECRET information on his laptop, the stuff that represents the company's lifeblood, and which can't be trusted to anybody else.

And this data isn't backed up on company file servers? What happens if the CEO's laptop gets dropped, or smashed by clumsy airport security, or stolen from him?

And you think they run a multi-billion dollar, Fortune 500 company this way? Seriously?

Do they have these things called "jokes" where you're from, guy? Or did you remove the part of your brain that understands figurative language?

Actually, what I did there was the opposite of "polarize", because I smooshed everything into one big group, in the middle. I don't know what the right word would be, though.

What I also did, more importantly, was take the piss out of Google, and apparently offend one of their fans (you).

I'm curious what basis you have to believe that "the people in charge at Google have more 'moral' business ethics than most'. Did you take a sample of businesses and rate the ethical practices of each? Or have you worked there, and seen how Google Sausage is made, and compared it to other companies for which you've worked?

I'm going to wear my colors, here, and guess that you're responding to the hard work that Google's brilliant PR department has but into their carefully polished corporate image.

But let's make this fun, I'll going to and make this simple challenge:

        What evidence can you provide to support your claim that Google is ethically superior to most other businesses?

and if you're game, you show me what you've got. (Feel free to define those terms however you want, it's your assertion, anyway.)

First, there's the outages. Google NEVER used to go down, it was part of their "mystique"--their engineering was SOOO amazing, and so well designed. The Cloud could NEVER go down!

Second, there's the Evil. I feel like I saw this one coming, years ago, having spent a good portion of my career in the advertising industry. It's a simple equation, right? Google is a publicly-traded company, and their core business is selling advertisements, which means their REAL business is selling your eyeballs+buying habits to anybody and everybody with cash. Eventually, there had to be some visible, significant conflicts between the basic reality and their high-concept, geek-chic PR fantasy.

Finally, and this is more personal, there's the lack of responsiveness from developers, and the perception of a "one-way street". Go look up the API for Google Tasks, and you'll see what I mean: Not only doesn't it exist, despite a lot of begging from interested users/developers, but Google keeps responding (when they do respond, which isn't often) that they have a corporate policy of not discussing pending release schedules. I understand that they have finite resources and have to make their own development roadmap, but their attitude seems to be "we're not going to acknowledge the gripes of our base". Which basically is the same attitude that any Big Software Company takes.

So, I'm not saying that Google is a crap company, or that I'm going to stop using Gmail, or that they're the new Evil Empire. But they're not really fundamentally different from every other Evil Corporation that we like to villify, here on Slashdot. There are no "good guys" and "bad guys"--there's just an open field of self-interested actors, each with a shitload more money, engineers, and lawyers than you.

Oh, and you checked alll of Google's server to be sure? Or did you randomly sample from a couple of hundred different points on the Internet?

Not to belittle the parent poster, but I think he thinks the world revolves around him.

"...code an app to use the modem as a phone..."

Like, a VOIP client, perhaps? I wonder whether anybody's ever bothered trying to write such an app...

"... no, 500 is not a large enough sample size to draw MEANINGFUL correlations."

Your statement is mathematically incorrect. Also, the way you misuse 'meaningful' suggests that you know nothing about probability and statistical inferences. Any 101-level, intro stats class at virtually any college will teach sample size calcuation in the first month or two. Honestly--it's so easy, they make Poli Sci majors take it.

"MEANINGFUL": How big is a "big enough" sample to be able to extrapolate to the larger population? It's a pretty straightforward math question, and it's been settled by proof for well over a century. The answer depends on three things:

  1) Higher levels of confidence require larger samples.
  2) Extremely small category sizes (e.g., 5% depression incidence) require larger sample sizes.
  3) Larger population sizes require larger samples.

#3 is the real bitch to understand, for most people. (WATCH CLOSELY HERE!) It's true that you need a larger sample to extrapolate to a larger population (all else being equal), BUT it's not a *directly* proportional relationship--the required sample size is proportional to a root of the population size. As in, if you double the population size, you DO NOT need double the sample size--you might only need to increase it slightly, by 1/10th or 1/100th.

Do you understand, yet? We're reaching the limits of what I can teach you, in this forum, so I would encourage you to take this up in a school setting and maybe learn a little more. But you know, I don't even think we've uncovered the real issue, yet.

I'm guessing that the study's results make you feel uncomfortable about yourself (this is Slashdot, after all). Is that what makes you get defensive and hostile, because you want to deny the study's implied judgement that YOU are fat, depressed, and such, because you're a gamer?

Sorry, man--if you're fat and sad, I feel bad for you, because I know that you didn't choose to be either of those things. It doesn't seem fair. But the fact is, life ain't fair, and denying it won't make you skinny or happy.

Wow, you kind of missed the point. The study actually makes 2 claims:

1) The average BMI, age, mental health index, etc. for the "gamer" population are ~ X, Y, Z, etc., and for the non-gamer population, they're ~ A, B, C, etc. (I don't know the exact values and standard error values, they aren't quoted in the article. But I'm sure that the researchers did calculate and publish them.)

2) The gamer and non-gamer populations truly differ W.R.T. BMI and mental health index. That is, the gamer/non-gamer samples differ enough for us to be confident that X>A, ZC, etc., and that any sample variations aren't just due to randomness.

You could certainly calculate the BMI, age, mental health index, etc. for the whole population. In fact, I'm sure that they DID this, in their study--you just take the weighted average of the gamer and non-gamer samples.

(Now, you might ask "What's the big deal about #2? After we've computed the gamer and non-gamer sample averages for each attribute, can't we just compare them and observer that gamers are sad-sack fatties?" But it's not quite that easy, unfortunately--the two sample averages might differ just due to random chance, so we have to use a statistical test to check how likely it is that the observed sample difference is due to random chance, alone.)

Sigh... It's not just you--vast swathes of other people, certainly the majority of the Western world, are ignorant of basic statistical concepts, just like you (no disrespect!). A sample size of 500 is almost certainly big enough for this kind of study.

For any given sample-extrapolation experiment, you can calculate a "conservative" sample size that will be "big enough" to meet your criteria for confidence level, confidence interval, etc. I just Googled this guy up, if you want to play around with some values, to see how big of a sample you need if you want to extrapolate to a population of 300,000,000:

  * http://www.surveysystem.com/sample-size-formula.htm

(PROTIP: It's smaller than you think.)

Wikipedia has an explanation of what/how/why, but I'll warn you ahead of time, unless you already took a stats class and just need a refresher, you won't understand (no disrespect!):

  * http://en.wikipedia.org/wiki/Sample_size#Estimating_proportions

For those too lazy to FTFL (no disrespect!), it takes somewhere around 1,000-2,000 sample members, if you want to get a 95% confidence level and a confidence interval of 5%, given a p/q split of ~ .5/.5. So assuming these researchers did their math correctly when they formally stated the results of their significance tests.

(NOTE: I'm NOT saying the study is valid--that's a whole 'nother Oprah. I'm just making a general statement about how big of a sample size a study needs to obtain a certain amount of probabalistic reliability.)