April 20, 2011
Honest!
What's infuriating about U.S. foreign policy isn't just its brutality, but the way it's accompanied by explosions of rhetoric about our love for All Humanity. Moreover, the rhetoric's always soaring yet bland, like watery vanilla pudding dropped on you from 30,000 feet.
So I appreciate this statement about Libya by Obama's Deputy National Security Adviser Denis McDonough, which I don't think has gotten enough attention:
"...we don't get very hung up on this question of precedent because we don't make decisions about questions like intervention based on consistency or precedent. We base them on how we can best advance our interests in the region."
Fair enough.
–Jonathan Schwarz
Posted at 11:43 AM | Comments (5)
Why We're So Great
It's not just that we train criminals while we put heroes in jail. Any picayune empire can do that. And it's not even that we train criminals and imprison heroes in the exact same place. It's that we imprison a hero for revealing our discussions with a criminal about how he was trained where we imprison the hero. EsherEmpire!
The Defense Department said Tuesday it would transfer Army private Bradley Manning, accused of providing classified documents to WikiLeaks, to a new detention facility at Fort Leavenworth in Kansas from the brig at Quantico, Va.
"The King [of Bahrain] related how his own experience at the U.S. Army Command and General Staff College at Fort LEAVENWORTH, Kansas had been one of the most personally and professionally rewarding of his life; he praised the value of continued military education opportunities."
–Jonathan Schwarz
Posted at 07:06 AM | Comments (9)
April 18, 2011
Tax Day Graphs
If I were teaching a class of smart 7th graders how to lie with statistics, I'd use the Heritage Foundation's Budget Chart Book. It includes everything you'd need in your toolbox if you wanted to bamboozle people in this particular way, yet it's simple enough that a 12-year-old could understand how they do it.
For instance, here's one of their charts:
The Top 10 Percent of Income Earners Paid 71 Percent of Federal Income TaxTop earners are the target for new tax increases, but the U.S. tax system is already highly progressive. The top 1 percent of income earners paid 40 percent of all federal income taxes in 2007, while the bottom 50 percent paid only 3 percent. More than one-third of U.S. earners paid no federal income tax at all.
The most important deception here is the phrase "U.S. tax system."* The federal income tax is, in fact, progressive. But it's by no means the entire U.S. tax system. There are also federal payroll taxes (regressive) and state taxes on income (generally flat), property taxes (generally flat) and sales (regressive). When all of that is added together, the system as a whole is only slightly progressive, and in fact is essentially flat from the middle quintile upwards. Here's a useful chart from Citizens for Tax Justice which includes all taxes:
* For extra credit, I'd have the smart 7th graders explain a less crucial but still important deception: whether there's any necessary connection between the (accurate) statistics Heritage gives about how much of the total federal income tax is paid by the top 1% and bottom 50%, and their statement in the previous sentence that taxes are "highly progressive." Obviously there isn't: we could have a flat tax, but if the top 1% earned 40% of all income, then they'd pay 40% of all income taxes. And if the bottom 3% only earned 3% of all income, then they'd pay 3% of all income taxes. Heritage doesn't want you to start thinking about that, so they leave out the percentage of total income earned by the top 1% and bottom 50%. (The top 1% earn about 24% of all income, up from about 9% in 1976.)
Here's another useful Citizens for Tax Justice chart that gives the relevant numbers for all taxes:
—Jonathan Schwarz
Posted at 03:42 PM | Comments (11)
April 14, 2011
We All Should Have Paid More Attention to Logarithms
By: Aaron Datesman
I had a little fun with graphs earlier this week. Perhaps you would like to have a little fun, too? If your idea of fun involves inputting tables of mortality statistics into an Excel spreadsheet, then it would be rude of me to keep all the fun to myself! So, why wait for me? Here are the mortality tables (use the code “140-205 Malignant Neoplasms”); and here is the US EIA data on the energy produced by nuclear power plants in the U.S. It will probably be a little while before I finish the analysis myself….
The idea I took away from that thought experiment about cancer rates and fallout (aka “emissions”) from commercial nuclear reactors is this: perhaps the dose relationship (for low doses) is logarithmic rather than linear. Mathematically, this is expressed for the excess death rate and total energy produced simply as
Since the energy produced is exactly proportional to the number of radioactive fission products created by the process, this is about equivalent to a relationship between dose and harm.
Having trained in physics, I like this – it reminds me of statistical thermodynamics. Although I had mono that semester, it’s rather natural to see a logarithm here – therefore it “feels” right. At a basic level, this is true because of a result known as the Central Limit Theorem. Physics undergraduates ordinarily encounter this in the context of the “random walk” problem, but it’s a universal statement about the distribution of results subject to a large number of statistically independent random events.
Perhaps it was clearer when I said that it “feels” right.
So, the interesting thought is this: perhaps the linear model for low doses should be replaced by a logarithmic dose (or exposure) relationship. Is this crazy? Well, actually I’m not the first person to think of it. The Radiation and Public Health Project made thisobservation about an evaluation of the health effects of the Three Mile Island accident which was published in 1997:
Plotting the O/E (Observed/Expected) ratios by level of exposure shows that the dose response does not conform to a linear model. Rather, a logarithmic or supralinear curve describes the relationship more accurately, as the greatest per-dose effects occur at the very lowest levels of exposure.
If I understand the graph below correctly, the author (Joe Mangano, whose analysis of thyroid cancer incidence I critiqued here) has fit a logarithmic relationship to the “Observed” data; the quality of the fit is determined by the vertical distance between the squares and triangles.
It may not be immediately clear, but a logarithmic model would be a very significant departure from the linear dose assumption upon which our judgments of safety are based. Using a linear model, for instance, reducing the dose by a factor of two reduces the health effects (typically, death) by the same factor. A logarithmic model, however, responds to a factor of two reduction in dose with a reduction in mortality by only an additive factor.
That is: if a logarithmic dose model applies, low doses of radiation are much more harmful than we currently believe.
So, how likely is it that our current operative understanding could be wrong? Well, the notoriously anti-nuclear organization known as the Federal Government of the United States of America has this to say about the health effects of low doses of ionizing radiation:
Since we cannot measure the stochastic [this means random, or non-deterministic, in the sense of the Central Limit Theorem - AD] effects of very low levels of exposure, health physicists must extrapolate the risks from what they know about high levels of exposure. Most radiation protection organizations estimate the risk of health effects from low levels of exposure, all the way to zero exposure, as proportional to those of high levels of exposure.
According to the Environmental Protection Agency, our beliefs about the safety of low levels of radiation are guesses based upon knowledge of the effects of high doses and the assumption of a linear dose model. Fortunately, I guess, we have the opportunity to assess whether that assumption of a linear dose model is correct – by graphing out the mortality statistics from a dangerous experiment we are performing on ourselves.
I actually don’t find that to be very much fun at all.
- Aaron Datesman
Posted at 11:19 PM | Comments (15)
Then They Came for Dana Milbank
For the past 20 years, as the U.S. middle class has quietly collapsed, Dana Milbank has made a great living as a media liberal who constantly ridicules liberals. But recently it seemed as though he'd suddenly noticed something was going on. Why? Because it was happening to him and his "brand-name MBA" wife, who were being screwed by Citibank after they'd refinanced their mortgage. (In fact, while he didn't mention it, his wife actually once worked for Citibank.) Now Milbank understood that "big banks" needed to be "brought to heel."
Except...after his brief encounter with reality, Milbank has gone right back to telling us what losers liberals are. Did you know the House Progressive Caucus has come up with some kind of preposterous socialist budget? But they didn't move the press conference inside even though it was raining! And they were all carrying umbrellas! What a bunch of nimrods! Ha ha ha ha ha ha oh crap look at the caller ID that's Citibank again ha ha ha ha ha ha!
First they came for the welfare mothers, but I did not speak out, because I was a member of Skull & Bones.
Then they came for middle-class manufacturing unions, but I did not speak out, because I had to get to a party at Marty Peretz's.
Then they came for the upper middle class people who didn't have columns in the Washington Post, but I did not speak out, because Dennis Kucinich is short.
And then they came for me...and I was STILL so fucking stupid that I spent my time making fun of the House Progressive Caucus.
—Jonathan Schwarz
Posted at 10:19 PM | Comments (28)
April 11, 2011
Morbid Fun With Graphs
By: Aaron Datesman
I wrote here about my dissatisfaction with the dose model, although probably without enough scientific support for the part everybody focused on at the end. (I’ll return to it eventually, since I think it’s pretty interesting. There were especially some smart comments which enhanced my understanding and helped to clarify my own thinking.) The post contained one other point which is at least equally significant: the dose model lumps the distinct biological effects of different kinds of emitters together into one number. This isn’t biologically justified; it’s “computationally convenient”.
Although I first encountered the linear dose model in 1996, I didn’t think to question it much until the end of my short career in the nuclear industry. My skepticism emerged during the last several months of 2005, which I spent writing a very long report on radiation effects in (non-biological) materials. As November slipped into December, and the stack of academic papers and government reports on my desk passed twelve, and finally twenty-four inches, I was overwhelmed with conflicting information about defect mechanisms, thermal healing rates, and dose measurements for different radiation spectra. So, what did my colleague and I do?
We did what engineers are trained to do: we picked the papers we understood the best, summarized the results for our bosses, and then constructed a linear model from which we extrapolated recommendations for experimental study. The report is still classified, or I would share it here. We were aware that our report failed to capture very much insight compared to all of the literature we had surveyed; but it’s standard operating procedure, so it’s what we did.
A silly but accurate explanation of the problem we confronted goes like this: the dose model takes apples (alpha), bananas (beta), and grapefruits (gamma), transforms them into pineapples, and then feeds us pineapples in all sorts of forms (in cake, as fermented juice, by throwing them at us, and many others), in amounts small and large, over time periods short and long, in order to determine whether we are allergic to apples, bananas, and grapefruit. If anything, this is a bigger problem for animate biological materials than it is for inanimate materials.
I think about this whenever I hear the claim that, since “background radiation” is safe, the small dose increment which human activities have added to the background (around several percent in most locations) also must be safe. This is wrong. For instance, a commenter pointed me toward the article “Cancer Incidence in an Area Contaminated with Radionuclides Near a Nuclear Installation”, which contains this worrisome piece of information:
The DOE station at the eastern (downwind) boundary of the plant has recorded an average concentration of 2072 attocuries/m^3 (aCi/m^3) of plutonium over the eight year period, compared to 32 aCi/m^3 for New York City….
That 32 aCi/m^3 of Plutonium measured in New York City is a small contribution to the activity of the background radiation, but understand this: there was never one atom of Plutonium on Planet Earth until humans made some. Even if the naturally-occurring background radiation (principally due to radon and cosmic radiation) is safe for humans (and we have no way to know this, since there can be no counterfactual), there is absolutely no scientific basis for lumping any amount of plutonium contamination into the natural background, and concluding that miniscule amounts of plutonium in the environment therefore are also safe.
It is absolutely unjustified. Not only is the conclusion of safety absolutely unjustified for plutonium, but it is also almost completely unjustified for other radioactive materials released by nuclear weapons testing and by releases from nuclear reactors, including strontium, cesium, and iodine. Converted to pineapples, the levels of these radionuclides are indeed small; however, compared to their near-zero natural abundances, the levels of these materials are vastly larger than any sensible definition of a “background” level.
But how to tell whether these low levels of released materials are harmful? Due to confounding factors including smoking, chemical exposure, and not calling your mother often enough, it’s essentially impossible to tell directly. The issue can only be resolved experimentally: for instance, by large-scale epidemiological (medical) studies. As a thought experiment, however, I might suggest shutting off all of the nuclear reactors all over the world while monitoring the rate of cancer mortality. Maybe even just turning them down would be enough, in fact.
I thought of this as I browsed through Annex C of the 2008 Report of the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR). It is one of the documents upon which George Monbiot bases his new pro-nuclear opinions.
I agree that the report is very interesting, although probably Monbiot and I did not find the same parts interesting. What I found interesting was the section about radioactive effluents from routine operations of nuclear reactors (pages 183-187). Somehow, despite my brush with the nuclear industry in 1996 and my employment in the industry in 2005, until recently I was under the impression that no such thing as releases of radioactive effluents due to the routine operation of nuclear reactors exists.
UNSCEAR also provides a handy graph, which I reproduce below. An interesting feature of the graph is that it provides a line for “Electrical energy generated”. You should note that, inherent to the process of generating power from fission, the more energy generated, the more radioactive byproducts are produced. (They don’t have to be expelled to the environment, but they must be produced. The relationship is proportional.)
Thanks to the internet, which makes many things easy that used to be impossible, it occurred to me to look up the incidence of cancer in the U.S. by year. I didn’t spend long on it; I’m sure I could find a better source. But all I wanted to do was to make two graphs, mash them together, and think about them. So, I did:
I acknowledge all sorts of problems with this scientifically, and myself don’t consider it anything more than a picture to go “Hmmmm…..” at. Therefore, although I’m tempted to write more about it, I think I’ll allow the graph above to speak for itself.
— Aaron Datesman
Posted at 06:08 PM | Comments (31)
April 09, 2011
TMI and Thyroid Cancer
By: Aaron Datesman
This post is about a report from the Radiation and Public Health Project about thyroid cancer. I admire the organization - especially their “Tooth Fairy Project”, which aims to track levels of strontium fallout - but I think the conclusions of their report are wrong. The alternative explanation I would like to offer relates to the Three Mile Island accident. It is a good illustration of the nature of fallout dangers, I hope, and certainly a cautionary warning (if true) about how corrosive an incorrect media narrative can be - even many years into the future. I will steal from the RPHP report to set the stage:
Thyroid cancer incidence is increasing more rapidly than any other malignancy in the U.S. (along with liver cancer), rising nearly threefold from 1980 to 2006. Improved diagnosis has been proposed as the major reason for this change by some, while others contend that other factors also account for the increase. Among U.S. states, 2001-2005 age-adjusted thyroid cancer incidence rates vary from 5.4 to 12.8 per 100,000. County-specific incidence data available for the first time document that most U.S. counties with the highest thyroid cancer incidence are in a contiguous area of eastern Pennsylvania, New Jersey, and southern New York. Exposure to radioactive iodine emissions from 16 nuclear power reactors within a 90 mile radius in this area as a potential etiological factor of thyroid cancer is explored; these emissions are likely a cause of rising incidence rates.
Uptake of radioactive Iodine-131, released from nuclear weapons tests and nuclear reactors, is accepted as a cause of thyroid cancer. (I recommend this article by Valerie Brown if you are unfamiliar with this topic.) Thyroid cancer is highly survivable, so it’s interesting to have incidence, rather than mortality, data. The table below is taken from the RPHP report. It lists the 18 U.S. counties with the highest rates of incidence of thyroid cancer. My childhood home of Lehigh County, PA, tops the list.
You’ll notice the eleven stars in the table. These are all counties clustered together in southeastern Pennsylvania, New Jersey, and downstate New York. This region contains the highest density of nuclear power plants in the country – thirteen operating reactors at seven distinct facilities.
In addition to this general argument, which you may find convincing, the report examines in greater depth incidence data for the area surrounding one reactor - Indian Point in Westchester County, NY. While Westchester County is not on the above list, the adjacent counties of Putnam, Orange, and Rockland all are. The authors find that the incidence of thyroid cancer in these four counties is more than 40% greater than in the rest of New York state. In 1976, the incidences were identical.
Aside from some discussion of other factors which may contribute (more on that in a moment), this is the conclusion to the report:
Geographic variations in mortality and incidence have been frequently used to reveal etiological factors for diseases. This report addresses the largely unexamined topic of geographic variation in U.S. thyroid cancer incidence and has identified proximity to nuclear plants as the most evident etiological factor. This finding is consistent with data in the U.S. National Cancer Institute study of cancer near nuclear plants, which documented consistent rises in thyroid cancer incidence in counties closest to nuclear plants after startup. Data in this report suggests that exposure to radioactive iodine released from nuclear plants is a factor in elevated and rapidly rising thyroid cancer rates.
This conclusion may be correct; there is probably information in the data presented which supports it. I do agree that iodine releases from operating reactors are certainly a matter of serious concern. However, the county-level data presented by RPHP support a much stronger explanation than the rather vague hypothesis regarding the regional concentration of nuclear reactors.
It’s not the fault of the authors that they overlooked this explanation. It’s the fault of the media, which for more than 30 years has failed to inform us regarding the true scope of the TMI disaster. This is from the section of the RPHP report which examines other sources.
Three Mile Island. Another source of exposure to radioactive iodine, especially in the northeast U.S. is airborne emissions from the 1979 accident at the Three Mile Island plant. Official reports estimated 14.2 curies of I-131 and particulates were released into the environment, and prevailing winds carried the radioactivity hundreds of miles to the east and northeast. But the 2001-2005 thyroid cancer rate Dauphin County PA, where the reactor is located, had a rate of 12.0, lower than many other counties in the state. Again, while 1979 Three Mile Island emissions may play a factor in subsequent thyroid cancer state and county, these data suggest it is not a major contributor.
There’s an interesting error here. The error also occurs in this article from the academic literature entitled “Incidence of thyroid cancer in residents surrounding the Three Mile Island nuclear facility.”
OBJECTIVES/HYPOTHESIS: On March 28, 1979, the worst nuclear exposure incident in U.S. history occurred near Harrisburg, PA. Small quantities of xenon and iodine radioisotopes were released into the environment from the Three Mile Island (TMI) nuclear power plant. The Pennsylvania Department of Health (PDoH) implemented a TMI Population Registry, including 32,135 individuals within a 5-mile radius of TMI, to track possible health effects to the local population. Although no increase in cancer mortality has been noted in this cohort, cancer incidence has not been tracked. Given the long latency period for the development of thyroid cancer after exposure to low-level radiation exposure, it is plausible that an increase in thyroid cancer incidence might just now be occurring…..CONCLUSIONS: Thyroid cancer incidence has not increased in Dauphin County, the county in which TMI is located. York County demonstrated a trend toward increasing thyroid cancer incidence beginning in 1995, approximately 15 years after the TMI accident. Lancaster County showed a significant increase in thyroid cancer incidence beginning in 1990. These findings, however, do not provide a causal link to the TMI accident.
Three Mile Island lies at the extreme southern tip of Dauphin County, adjacent to both York and Lancaster Counties. Since fallout dispersion patterns are determined by the wind, it’s suspicious to base an argument about fallout and fallout effects in Dauphin County on TMI’s location in Dauphin County. When I got the idea in my head that the authors of these papers may not have examined the geography very carefully, I graphed it out myself. You may want to compare the map below to the map in this postabout the article in Science (Wahlen et al.) discussing TMI fallout measured in Albany.
The counties are labeled according to their rank in the incidence chart. (I grew up in the county labeled “1”.) I don’t see much evidence here that the regional concentration of nuclear power plants is related to the incidence of thyroid cancer. Of the seven regional nuclear facilities, only Peach Bottom in Delta, PA, is located in one of the counties highlighted in red. Although I believe the argument that TMI fallout might not land in Dauphin County, I don’t believe that all nuclear plants by necessity are sited on county boundaries. (I may be wrong about this. If somebody would care to look this up, I would appreciate the favor.)
There are not any nuclear power facilities in Lehigh(1), Northampton(3), and Bucks(14) Counties, although it is true that none of those locations is very far away from the Limerick power station in Montgomery County (which is not itself in the top 18). However, if routine (and even permitted) emissions of radioactive iodine are the fundamental cause, it’s very hard to explain why Lehigh County(1) and Lancaster County(18) both have high rates, while Berks County between them does not.
A much likelier explanation is a single, large emission of radioactive iodine which, due to geographical variations in the weather, resulted in an inhomogeneous pattern of fallout. In short, on the day of the Three Mile Island accident, there was scattered rain in southeastern Pennsylvania and downstate New York. You’ll notice that the three clusters (7/18, 1/3/14, and 4/5/8) of red lie quite well along a track parallel to the weather track for 28 March 1979 described in the previous post.
That’s one error based upon careful analysis of geography. (It’s perhaps something only a hometown boy would think of.) There’s possibly a second error, also. What if the estimate of the emissions of Iodine-131 due to the Three Mile Island accident were wrong– by a factor of more than 50,000?
For example, the official story is that the TMI incident released only 13 to 17 curies of dangerous iodine into the outside environment, a tiny fraction of the 13 million curies of less dangerous radioactive gases officials say were released, primarily xenon. Such a number would seem small compared with, for example, the 1986 nuclear accident at Chernobyl, which released anywhere from 13 million to 40 million curies of iodine and is linked to 50,000 cases of thyroid cancer, according to World Health Organization estimates.But the Thompsons and Bear point out that the commission's own Technical Assessment Task Force, in a separate volume, had concluded that iodine accounted for 8 to 12 percent of the total radioactive gases leaked from Three Mile Island. Conservatively assuming the 13 million curie figure was the total amount of radioactive gases released rather than just the xenon portion, and then using the Task Force's own 8 to 12 percent estimate of the proportion that was iodine, they point out that "the actual figure for Iodine release would be over 1 million curies" - a much more substantial public health threat.
I included on the map historical weather data for Allentown, PA (in the county labeled “1”) and Poughkeepsie, NY (a bit north of county “8”). The information that there were scattered showers in New York and Pennsylvania on 29 and 30 March 1979 is significant because rainfall is the principal means by which radioactive fallout actually falls to earth. The below is excerpted from a report by the National Cancer Institute titled Whatever It Looked Like, We Didn't Drop Bombs on You: So Why Worry? Oh, no. I mean, titled Estimated Exposures and Thyroid Doses Received by the American People from Iodine-131 in Fallout Following Nevada Atmospheric Nuclear Bomb Tests .
Precipitation, hereafter used interchangeably with the words rain or rainfall, efficiently scavenges particles suspended in the atmosphere and can result in much greater deposition than that due to dry processes such as sedimentation, impaction, and diffusion. However, although a substantial fraction of the amount of radioactive materials present in the air may be scavenged by rainfall at particular locations, the fraction of the whole radioactive cloud so removed during one day is small.Nuclear weapons were detonated when dry weather was predicted so that the deposition of radioactive materials onto the ground in the vicinity of the NTS would be as low as possible. However, because dry conditions were seldom maintained over the entire U.S. for several days after each shot, rainfall represents the primary means by which 131-I was deposited east of the Rocky Mountains.
The report makes very disturbing reading. Of course, so does this testimony belonging to Robert and Lena Zeigler of York Haven, PA, found on the Three Mile Island Alert web site:
ROBERT: And another thing I want to tell you. This patio out here. The very second day it rained. I never in my life seen it before. Where that rained on that patio, it was as purple as that towel there.LENA: A reddish brown.ROBERT: Just like you took maybe a spoonful of blood and dumped maybe a quart of water in it. And that went on there for a year or so, wasn’t it. It was the same thing every time. You could see it as soon as it rained. It’s still not clean. See what I mean. Now here, I had a lifetime roof put on here. It’s a sixty pound weight tin. The man told me it was a lifetime guarantee. I could go up there a month after this [accident] happened and just punch holes in my roof. It just ate that roof right up.
York Haven is in York County(7), very near to Three Mile Island. You are no doubt aware of what color water takes on when iodine compounds are dissolved in it. I will only add that, although we add it to salt, iodine is quite toxic (a lethal dose is 4 grams) and highly corrosive to metal.
It’s very plausible that the high rates of incidence for thyroid cancer in southeastern Pennsylvania and downstate New York identified by the Radiation and Public Health Project are due to fallout from Three Mile Island. As one final piece of supporting evidence, I offer this summary of the weather conditions around TMI on the day of the accident, March 28, 1979. This is taken from the Science article “Radioactive Plume from the Three Mile Island Accident: Xenon-133 in Air at a Distance of 375 Kilometers”:
For the first release period on 28 March, the meteorological conditions at Middletown were rather stagnant, with medium- to low-speed winds gradually shifting from northwesterly to northeasterly to easterly and finally to southeasterly. From 29 to 31 March, southwesterly winds prevailed at increased speed.
Following that description, a release from Three Mile Island on 28 March would have been blown over York(7) and Lancaster(18) Counties before assuming a track toward the northeast. I believe that is the story the map above tells as well.
(Full disclosure: the piece of this I can’t figure out is why the scientists in Albany didn’t detect any Iodine-131. If anyone can puzzle this out, please let me know.)
— Aaron Datesman
Posted at 12:28 AM | Comments (26)
April 08, 2011
Glenn Greenwald, Unicorn
By: John Caruso
It seems all my postings lately involve the avoidance of being remiss, and that's what I'd be yet again if I didn't highlight this bit ofcommentary from Glenn Greenwald:
[I]f you were a Democratic Party official, wouldn't you also ignore -- and, when desirable, step on -- the people who you know will support you no matter what you do to them? That's what a rational, calculating, self-interested, unprincipled Democratic politician should do: accommodate those factions which need accommodating (because their support is in question), while ignoring or scorning the ones whose support is not in question, either because they will never vote for them (the hard-core right) or will dutifully canvass, raise money, and vote for them no matter what (the Democratic base). Anyone who pledges unconditional, absolute fealty to a politician -- especially 18 months before an election -- is guaranteeing their own irrelevance.
Why does this sound hauntingly familiar to me? Oh, right, because of this and this and this and this and I think we'd both agree that's enough of that for now, wouldn't we. I've spent so much time riding this hobby horse because I've always felt it's one of the most important domestic political questions (if not the most important). Or as Greenwald puts it, it's "one of the most important domestic political questions (if not the most important)". Gaaah! Stop doing that!
As I've said before, I give Greenwald tremendous credit for continuing to follow his principles wherever they lead even now thatPresident Fleshword has taken up residence in the White House. It's a rare person—and a downright unicornesque high-profile liberal blogger—who chooses that path over partisanship. And he's paying a price for it; I regularly see him being slagged in the comments sections of liberal blogs and media outlets for the exact same kinds of observations that won him ringing praise when he was applying them to Bush. If he keeps this up, he may find that instead of writing for Salon he's reduced to tapping out his opinions on some obscure blog somewhere. Ha ha ha ha! Oh, wait.
— John Caruso
Posted at 01:10 PM | Comments (29)
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