Hit and Run

Got another “hit and run” attack the other day. I won’t link to it, because I see no need to improve the notoriety or the pagerank of the hack who penned it, but you can find it on technorati if you’re interested.

A “hit and run” attack is where a blogger pens an opinion about you or your writing, you comment and…. then nothing. These posts are a waste of time and energy, and because they masquerade as legitimate opinion, they worsen the signal-to-noise ratio of the blogosphere.

I’m excited when I see an opinion or comment about something I’ve written, because it gives me the opportunity to improve what I believe. That’s why I started this blog.

Coming across these energy-vampires is taxing. (Actually, bandwidth-vampire too, as the supposed “vice president in the software energy” direct-linked to an image.)

Still, these second-rate academics (supposedly he’s a PhD, as well) are good for putting things in perspective. Aside from the thread where I made the mistake of posting two comments, nothing he’s written this year has generated a comment.

Meanwhile, just looking on this blog’s right side, I get great commentators like Michael, Jayson, Steve French, Stephen Pampinella, Adam, biz, nykrindc, Dan McIntosh, and more.

The greatest fortune you can have in life (besides a good family) is having friends smarter than yourself. I like to think that my habit of responding to what people say has helped me achieve that.

6 thoughts on “Hit and Run”

  1. I stumbled upon the thread in my feedreader, I will just post my comments here from now on:

    Dan:

    I like where your methodology is going (quantitative is golden). I see a few problems you need to take into account:

    1. Weighing: Currently, if I am reading it correctly, all your DPs are weighed equality. However, the importance of the different DPs are not equal. The way you have it now, your data management is actually probably causing more of an effect as the variables themselves.

    2. You are using all domestic data, however “neighborhoods matter”. Try including a binary of whether any countries bordering the state have had a war in the last five years. There are lots of good research out there on this.

    3. (and this is really KingDaddy's point), Your model has to address both the succeeding states inside the gap and the failing states outside the gap.

    I think if you took into account just the first two points the map would look very different, and Botswana would be removed from the gap.

    I'll check this post later today.

    P.S. Calling the poster's comments a “hit and run” is slightly over-dramatic.

  2. I'm all for poking holes in the ideals and strategies that hold the most conviction but I've presented a simple question there and only one chap has answered and he admits to “skim-reading”. So I guess I'll put it down here. Of all the critics who weighed in how many actually have read Barnett beyond occasioning his blog?

  3. Jayson,

    Yeah. You are.

    Jay,

    Agreed.

    Chris,

    Thanks for your comments, regarding my test of the core/gap model [1]!

    I liked your clean organization into four subpoints, so I'll answer those individually

    1) “Currently, if I am reading it correctly, all your DPs are weighed equality. “

    I was interested that Barnett created a categorization model based on service response days, and then provided metrics that supported such a scheme. I'm sure there are better methods of testing and operationalization the variables, but I was impressed not only did the core/gap model pass face analysis, but that it produced falsifiable hypohesis that not only generally supported the model, but generated further hypotheses (such as my contention that the “Gap” may just be the set of African and Islamic states)

    2) “Try including a binary of whether any countries bordering the state have had a war in the last five years.”

    What dataset/threshold of violence would you use. (A serious question. I've been focusing on psychological studies recently, but it would be interesting to see if that data is availabl.)

    3) “Your model has to address both the succeeding states inside the gap and the failing states outside the gap.”

    Not really. Think of core/gap as a condition, but as a factor: great at explaining between-group differences, not great at explaining within-group differences.

    4) “Try including a variable on income inequality (Gini Coefficient is good). That might take care of some of the outliers.”

    A superficial glance [2] doesn't show a matchup between core/gap — my guess being that income inequality can be an outcome of economic growth more than economic wealth.

    Finally)

    “P.S. Calling the poster's comments a “hit and run” is slightly over-dramatic.”

    Would “a dictation disguised as a dialogue waste of my time?” have been less dramatic? 😉

    [1] http://www.tdaxp.com/archive/2006/05/08/redefining-the-gap-1-prologue.html
    [2] http://en.wikipedia.org/wiki/Image:World_Map_Gini_coefficient.svg

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