Anti-conservative bias and social psychology

My most popular blog post of all time was the one I did on conservative trust in the scientific community vs retraction rates.   I called it "Paranoia is just good sense if people really are out to get you" because I had a suspicion (confirmed when I ran the data) that conservatives might actually be behaving rationally when they said they trusted science less, given the ever increasing retraction rates in prominent journals.

Now, a new study shows that this distrust of the scientific community is even more well founded than I originally thought.

In a survey conducted by two self proclaimed liberals, it was found that there is heavy evidence that conservatives are being systematically discriminated against in the field of social psychology.  What unnerved the authors even more is that this was not a case where people were hiding their bias:

To some on the right, such findings are hardly surprising. But to the authors, who expected to find lopsided political leanings, but not bias, the results were not what they expected.
"The questions were pretty blatant. We didn't expect people would give those answers," said Yoel Inbar, a co-author, who is a visiting assistant professor at the Wharton School of the University of Pennsylvania, and an assistant professor of social psychology at Tilburg University, in the Netherlands.
He said that the findings should concern academics. Of the bias he and a co-author found, he said, "I don't think it's O.K."

The study isn't available yet, so I can't say I've read the nuances.  Still, it's hard for me to believe two liberal authors would have attempted to skew the results in this direction.  Conservatives have claimed this bias exists for years (look no further than the ethics complaint lodged against Mark Regnerus for proof), and will no doubt find nothing shocking about the results.  For liberals to have to face what this means however, that's something new.  Even in the comments on this article, the vitriol is surprising, with many saying that conservatives are so out of touch that it is an ethical responsibility to keep them out of fields like social psychology.

Yikes.

It is much to my chagrin that social science gets lumped in with harder science, but since findings in this field are so often reported in the media, it makes sense to take them in to account.  We have a vicious cycle here now where some fields are dominated by one party, who then do studies that slam the other party, then accuse that party of being anti-science when they don't agree with the results.  This is crazy.  The worst thing that can happen to any scientific research is too much consensus....especially when it involves moving targets like social psychology.  With 40% of the population identifying as conservative, how can we leave those perspectives out?  Everyone, liberal and conservative, should be troubled by these findings.  Those untroubled by this should take a good look at themselves and truly ask the question "what am I so afraid of?".

International data - beware the self reporting

Maybe it's just because the Olympics are on, but I've run in to a few interesting international statistics lately that gave me pause.

The first was regarding infant mortality.  After Aaron Sorkin's new show The Newsroom incorrectly reported that the US was 178th in infant mortality (really, you think there are 177 countries you'd rather give birth in?), I went looking for the infant mortality listings across the world.  The US does not typically do very well in terms of other industrialized countries.  

There are a few interesting reasons for that....we have a much larger population than most of the countries that beat us, and it's spread out over a much larger area.  Our care across areas/populations tends to be more uneven, states vary wildly on issues like access, health insurance, prenatal care, etc. Our records however, tend to be meticulous....there is very little doubt that we capture nearly all infant mortality that actually occurs.  This combination can put the US at a huge disadvantage in these statistics (10-30% according to the best published studies).

This raises the point of why Cuba tends to beat us.  Now, realistically speaking, if you or someone you love had to give birth, would you seriously pick Cuba over the US?  Would anybody?  And yet they look safer given the data....which is all self reported.  I have no problems believing that Singapore outranks us, but I'm skeptical of any country that might have an agenda.  Worldwide, there is actually very little consensus on what is a "live birth", and the US tends to use the "any sign of life" definition.  

On the other end of the spectrum, I saw this piece recently on gun control.  I've covered misleading gun stats before (suicides are often combined with homicides to get "death by gun violence" numbers).  One of the interesting facts the article above points out is that internationally, gun deaths are only counted when it's civilian on civilian violence.  This is certainly fine in the US...I would think we wouldn't want to count every time the police had to open fire, but in countries with, um, more questionable police tactics, this could cause some skewing (Syria was cited as one such example).  

Data is hard enough to pin down when you know the sources have no vested interest in misleading you....international rankings will never be free from such bias.

Review and redraft - research in government

A few months ago, my father let me know that New Hampshire had passed a law that required the various government agencies to update their rules/statutes every few years (5 years? 7 years? Dad, help me out here).  I'm not entirely sure what the scope of this law was, but my Dad mentioned that it was actually quite helpful for his work at the DMV.  It had surprised him how many of their rules did not actually reflect the changing times, and how helpful it was to update them.  One of the biggest rules they had found to update was that in certain situations, they were still only allowed to accept doctor's notes from M.D.s....so anyone who used a nurse practitioner for primary care couldn't get an acceptable note....despite NPs being perfectly qualified to comment on the situations they were assessing.  It wasn't that the note needed to be from an MD, it was just that when the rule was written, very few people had anything other than a primary care MD.  I found the entire idea pretty good and proactive.

I was thinking about that after my post yesterday on South Dakota's law regarding abortion risk disclosure.  I was wondering how many, if any, states require that laws based primarily on current scientific research  review those laws in any given time period.

Does anyone know if any states require this?  Or is this solely up to those who oppose certain laws to challenge things later?  

Correlation and Causation - Abortion and Suicide meet the 8th circuit

Perhaps it's lawyer's daughter in me, but I think watching courts rule on presentation of data is totally fascinating to me.

Today, the 8th Circuit Court of Appeals had to make just such a call.

The case was Planned Parenthood v Mike Rounds and was a challenge to a 2005 law that required doctors to inform patients seeking abortions that there was "an increased risk of suicide ideation and suicide".  This was part of the informed consent process under the "all known medical risks" section.

Planned Parenthood challenged on the grounds that this was being presented as a causal link, and was therefore was a violation of the doctor's freedom of speech.

It's a hot topic, but I tried to get around the controversy to the nuts and bolts of the decision. I was interested how the courts evaluated what research should be included and how.

Apparently the standard is as follows:

...while the State cannot compel an individual simply to speak the State’s ideological message, it can use its regulatory authority to require  a  physician to provide  truthful,  non-misleading  information relevant to a patient’s decision to have an abortion, even if that information might also encourage the patient to choose childbirth over abortion.”  Rounds, 530 F.3d at 734-35; accord Tex. Med. Providers Performing Abortion Servs. v. Lakey, 667 F.3d 570, 576-77 (5th Cir. 2012).  

So in order to be illegal, disclosures must be proven to be "“either  untruthful, misleading or not relevant to the patient’s decision to have an abortion."


It was the misleading part that the challenge focused on.  The APA has apparently endorsed the idea that any link between abortion and suicide is NOT causal.  The theory is that those with pre-existing mental health conditions are both more likely to have unplanned pregnancies and to later commit suicide. It was interesting to read the huge debate over whether the phrase "increased risk" implied causation (the court ruled causation was not implicit in this statement).


Ultimately, it was decided that this statement would be allowed as part of informed consent.  The conclusion was an interesting study in what the courts will and will not vouch for:

We acknowledge that these studies, like the studies relied upon by the State and Intervenors, have strengths as well as weaknesses. Like all studies on the topic, they must make use of imperfect data that typically was collected for entirely different purposes, and they must attempt to glean some insight through the application of sophisticated statistical techniques and informed assumptions. While the studies all agree that the relative risk of suicide is higher among women who abort compared to women who give birth or do not become pregnant, they diverge as to the extent to which other underlying factors account for that link.  We express no opinion as to whether some of the studies are more reliable than others; instead, we hold only that the state legislature, rather than a federal court, is in the best position to weigh the divergent results and come to a conclusion about the best way to protect its populace.  So long as the means chosen by the state does not impose an unconstitutional burden on women seeking abortions or their physicians, we have no basis to interfere.

I did find it mildly worrisome that the presumption is that the state legislators are the ones evaluating the research.  On the other hand, it makes sense to put the onus there rather than the courts. It's good to know what the legal standards are though....it's not always about the science.

Political ages...mean vs median?

I just found out The Economist has a daily chart feature!

Today's graph about age of population vs age of cabinet ministers is pretty fascinating:

It did leave me with a few questions though.....who did they count as cabinet ministers?  I don't know enough about the governments in these countries to know what that equates to.  Also, why average vs median?  

I initially thought this chart might have been representing Congress, not the Cabinet.  I took a look at my old friend the Congressional Research Service Report and discovered that at the beginning of the 112th Congress in 2011, the average age was  57.7 years, which would make this chart about right.  I had to dig a bit further to get the ages of the Cabinet, but it turns out their average age is 59.75.  I was surprised the data points would be so close together actually....especially since that 57.7 was for Jan 2011, so it's actually 59.2 or so now.  

In case you're curious, 7 members of the cabinet are under 60.  The youngest is Shaun Donovan (46), Department of Housing and Urban Development.  The oldest is Leon Panetta (74), Department of Defense. Panetta is actually the only member over 70.  Half of them are in their 60s, 5 in the 50s, and 2 in their 40s.  

I felt a little ashamed I only could have given name/position to 5 of them before looking them all up.  That's not great, especially when you realize I'm counting Biden.  Still, I comforted myself with the fact that I bet that beats a very large percentage of Americans.  

A quick look for other data suggests that median age of populations is the more commonly reported value.  The median age of the cabinet was actually 61, in case you're curious.

Political Arithmetic - Voter ID laws

Update: Link fixed

Last week I put up a post slamming an infographic on fair market rent between states.  I was interested in the AVIs response, which end with "These are advocacy numbers.  Not the same as actual reality."

Advocacy and other political skewings of data are one of those things that shouldn't bother me, but do.  

I read headlines, knowing that I'm going to be driven nuts but the presumptions and projections, and yet I read things anyway.  It's a bad habit.

All that being said, I truly enjoyed Nate Silver's examination of the real effect voter ID laws might have on voter turnout in various states. 

He attempts to cut through all the partisan hoopla and to do a one person point-counterpoint.  An example:

But some implied that Democratic-leaning voting groups, especially African-Americans and Hispanics, were more likely to be affected. Others found that educational attainment was the key variable in predicting whom these laws might disenfranchise, with race being of secondary importance. If that’s true, some white voters without college degrees could also be affected, and they tend to vote Republican.

He also makes a fascinating point about the cult of statistical significance:

Statistical significance, however, is a funny concept. It has mostly to do with the volume of data that you have, and the sampling error that this introduces. Effects that may be of little practical significance can be statistically significant if you have tons and tons of data. Conversely, findings that have some substantive, real-world impact may not be deemed statistically significant, if the data is sparse or noisy.

On the whole, he concludes it will swing in the Republican direction for this election, but reminds everyone:

One last thing to consider: although I do think these laws will have some detrimental effect on Democratic turnout, it is unlikely to be as large as some Democrats fear or as some news media reports imply — and they can also serve as a rallying point for the party bases. So although the direct effects of these laws are likely negative for Democrats, it wouldn’t take that much in terms of increased base voter engagement — and increased voter conscientiousness about their registration status — to mitigate them. 

The whole article is long but a great read about how to assess policy changes if you're trying to get to the truth, rather than just prove a political point.

The SCOTUS and perception of statistics

Finally got internet in the new house.  Can't complain too much....the guy finished running the wire to our house even though a thunderstorm started.  Clearly that man was getting paid by the job, not the hour.

Anyway, had an interesting chat with my father (a lawyer) after our closing on Thursday about the Supreme Court ruling on health care.  He mentioned that a coworker was griping that the Supreme Court meant nothing any more because they only voted on party lines.  My father, being the good data accuracy man that he is, quickly dissented.

He looked it up, and asserted that nearly half of the decisions last year were unanimous.  For this year, 7-2 votes were the least common (8%), then 8-1 (11%), 6-3 (17%) and then 5-4 (20%).  So overall,  they agree nearly as much as they disagree, and they are only completely divided on about 1 in 5 cases.  Kennedy and Roberts voted with the majority over 90% of the time.  Ginsburg was the least likely to vote in the majority.  Lots of interesting stats to be run on this, another good breakdown of some of the data is here.

It seems the perception that every vote is political is heavily skewed by the very few court cases most of us hear about every year.  I would wager even highly political citizens probably couldn't rattle off more than a handful.  When you break down the 5-4 decisions exclusively, about 2/3rds of them vote down ideological lines.....which totals to about 10 cases for 2011.

This kind of skewing of perception is common when a few high profile events dramatically overshadow regular operations.  Thanks Dad, for pointing that out.

Big day

To be honest, my day was dominated by big news that had nothing to do with healthcare.....we closed on our house today (the one we were buying....we closed our sale yesterday).  

I was fairly glad, as I got sick of the coverage of the decision by noon.  

I thought the coverage itself had some interesting things to say about how we process data however.  When it comes to science, so often people are just skimming over things, trying to get out a good headline.  Watching the blogs and other websites today, I saw a different angle....people trying to dissect legal jargon quickly to get to the sound bite....which of course led to this:

It was almost nice watching this happen in a different field....though I felt incredibly bad for the pundits trying to put together commentary while still trying to read the decision.

Not much with statistics to comment on, though Nate Silver has some good preliminary stats on how this will go for the election.  

More thoughts on the soda ban

Yesterday I found out the soda ban is potentially hitting a bit closer to home.

For those of you not familiar with Cambridge, MA, it's affectionately known as "The People's Republic" (and even has a communist bar of the same name).  Thus the proposed ban was pretty unsurprising.

Coincidentally, Ben Goldacre put up a new post yesterday publicizing a paper he coauthored to try to push governments in the UK to actually conduct trials of their policies before implementing them.

Best quote:

We also show that policy people need to have a little humility, and accept that they don’t necessarily know if their great new idea really will achieve its stated objectives. We do this using examples of policies which should have been great in principle, but turned out to be actively harmful when they were finally tested.

Contrast this to the Mayor of Cambridge's statement on the soda ban:

"As much free will as you can have in a society is a good idea," Davis said Tuesday. "... But with a public health issue, you look at those things that are dangerous for people, that need government regulation."

Is no one interested in finding out if this idea will actually work before implementing it?  The leading researchers in the field seem to think it won't.   I tend to agree with them.  You know what though?  I'm game.  Let's put it to a randomized trial.  There are those who think the constitutionality of this should be worked out first, but I think a well run trial could open the door for an opt in system rather than a mandatory one.

Hey, maybe if politicians stayed a little more open to testing their ideas, you wouldn't wind up with cartoons like this one:

Soda bans and research misapplications

When I first read about Mayor Bloomberg's proposed soda restrictions for NYC, I immediately thought of this post where I mentioned the utter failure of removing vending machines from schools.  Thus, I was extremely skeptical that this ban would work at all, and it seemed quite an intrusion in to private business for what I saw as an untested theory.

To be honest, I didn't put much more thought in to it.  I saw the studies about people eating more from large containers floating around, but I dismissed on the basis that (like with the vending machine theory) they were skipping a crucial step.  Even if this ban got people to drink less soda, that doesn't actually prove it would reduce obesity.  You have to prove all the steps in the series to prove the conclusion.

A few days ago, the authors of the "bigger containers cause people to eat more" study published their own rebuttal to the ban.  In an excellent example of the clash of politics and research, they claim that to apply their work on portion sizes in this manor is a misreading of the body of their work.  They highlight that the larger containers study was done by assigning portion sizes at random, to subjects who had no expectations as to what they would be getting.  In their words, the ban is a problem because (highlight mine):

Banning larger sizes is a visible and controversial idea. If it fails, no one will trust that the next big -- and perhaps better -- idea will work, because "Look what happened in New York City." It poisons the water for ideas that may have more potential.

Second, 150 years of research in food economics tells us that people get what they want. Someone who buys a 32-ounce soft drink wants a 32-ounce soft drink. He or she will go to a place that offers fountain refills, or buy two. If the people who want them don't have much money, they might cut back on fruits or vegetables or a bit of their family meal budget.

In essence, by removing the random element and forcibly replacing what people want with something the don't, you frequently will have the worst possible effect: rebellion.

Mindless eating can be a problem, but rebellious eating is even worse.

When the researchers you're trying to use to back yourself up start protesting your policies, you know you got it all wrong.

How long do you study to become one of the cultural elite?

I took one class on assessment in my master's, and it gave me a whole new respect for teachers (or anyone who routinely prepares questionnaires for people).

Figuring out how to assess whatever topic you're assessing is really really hard.

That being said, I found this quiz particularly interesting.  It's called "Do You Live In a Bubble?", but it's target is particularly the "new upper class" and how much they do or do not understand about the lives of most Americans.

What he chose to assess is fairly interesting....people you know, where you've lived, smoking and drinking patterns, jobs you've had, knowledge of popular media, etc.  Lots of interesting issues to be taken with those categories, especially for those who clearly didn't get the score they were hoping for.  The comments are pretty amusing actually...I feel like one of the questions should have been "is it important to you that this quiz tell you that you are "of the people"?

The most interesting point here was actually the entire purpose of the quiz.  The author of the quiz answered a few follow up questions, but I thought this was the most telling one:

2. Do you feel that people scoring higher on the quiz are not culturally sequestered as well? 

Question from Reddit: HillbillyThinkTank[S]: "You're right that everyone lives in a bubble of some kind; the tendency to cluster with similarly situated people is not a behavior limited to the "elite." The way the quiz is structured, he is suggesting that a low-scoring person is culturally sequestered in a way that a high scoring person is not. I don't think I agree with that." 

Sure, they're sequestered. We all live in bubbles of one kind or another. The problem is an asymmetry. As I put it in the book, it isn't a problem if a truck driver doesn't understand the priorities of a Yale law professor, or news anchor, or cabinet secretary. It's a problem if the ignorance is the other way around, because the elites are busily affecting the lives of everyone else. When they haven't the slightest idea what the rhythms and feel of life are like in mainstream America, they tend to make mistakes.

I thought this was an interesting case of trying measure a very abstract concept through concrete questioning.  He includes an explanation of each question and why it was included.

Agree or not with his questions, it certainly succeeds at being provocative.

Also, in case you're curious, I scored a 56.

Researching New Family Structures...Cutting Through Politics with Facts

I've been reading Bad Science by Ben Goldacre, and I highly recommend it.

In it, he quotes an interesting study regarding how likely people are to pick apart studies that challenge their preconceived notions.  Unsurprisingly, people are far more likely to notice flaws in studies they don't agree with than those they do.  He then made a somewhat tongue in cheek suggestion that perhaps all papers should have to list the method section first, to make sure that it was assessed before you knew what the conclusion was.

That came to mind today when I was reading Mark Regnerus's explanation of his new research in to new family structures.

I was unsure what to think of this study just from the headline.  I've actually read some of Regnerus's research in the past and disliked it, so I wasn't sure what I'd think of his take on this issue.

I found the paper fascinating.

Part of his premise started from his observation that adoption presents a unique challenge for parents, as is well acknowledged by research.  Thus, it interested him that many studies on gay and lesbian parenting showed no differences between that and heterosexual couples.  That appealed to my data analysis side, it's certainly not an observation I would have put together right away.  The study was focused on the young adult (18 to 39) population, and thus the slightly longer term outcomes of products of these families.

What impressed me so much about this study was how many pains they took to correct methodological errors in previous studies.  With such a highly politically charged topic, it would have been easy for him to just shy away from this study.  While critics were quick to point out that his funding came from two conservative organizations, his conclusions are not necessarily conservative.  While he does find that the outcomes for children of gay parents have worse outcomes on most metrics*, he acknowledge the high level of broken homes from these parents as a huge contributing factor.  His population makes the study a bit retrospective, and he acknowledges these limitations.  From his Slate.com article:

Let me be clear: I’m not claiming that sexual orientation is at fault here, or that I know about kids who are presently being raised by gay or lesbian parents. Their parents may be forging more stable relationships in an era that is more accepting and supportive of gay and lesbian couples. But that is not the case among the previous generation, and thus social scientists, parents, and advocates would do well from here forward to avoid simply assuming the kids are all right.

 William Saletan (and others) have quickly responded with the idea that this study actually supports the need for gay marriage by proving that the broken homes of the past were damaging to children.  Clearly Regenrus does not rule that out in his study....he is quite clear that he knows the selected age group covers only those children born 1971 to 1994 (pre legal gay marriage), and he goes very in depth with the broken homes angle.....acknowledging that many of the broken homes were fractured hetero marriages that preceded the same gender relationships.

The value of a study like this however, is not merely in the conclusions.  The value is that it unsettles the debate, and hopefully precipitates a response from those who disagree with him.  In emotionally and politically charged fields, the response to data should be newer and better data that corrects the perceived problems in the last study.  Politics should not be a reason to consider something "settled", and we need researchers who are at least willing to entertain the other side, if only to give people something to respond to.

I know most people will not make up their mind on this issue because of a research study, but I don't think that's a reason to not do research. Whatever a person believes, I would hope this study could be read with unbiased eyes, methods first....just to see what you think.

*As I commented in this post metrics on child rearing can be hard to determine.  Some of the ones used in this study were: being unemployed, less healthy, more depressed, more likely to have cheated on a spouse or partner, smoke more pot, had trouble with the law, report more male and female sex partners, more sexual victimization, and were more likely to reflect negatively on their childhood family life.  The full list is in the paper here.

Quote of the week and more recall coverage

Statistics are like bikinis.  What they reveal is suggestive, but what they conceal is vital.  ~Aaron Levenstein

I've been reading more of the Scott Walker recall election coverage, and was struck by the frequent references to Walker being "the first governor to survive a recall election".  Of course this made me curious how many governor's had been recalled.  I remembered the California governor a few years back, so I had been imagining it would be at least a dozen or so.

Nope.

It's two.  Lynn Frazier from North Dakota in 1921, and Gray Davis from California in 2003.

I had to laugh at my own sampling bias.  My assumptions were pretty understandable....I've been of voting age since 1999, and in that time this has happened twice.  Therefore it was reasonable to assume this happened at least occasionally.   I figured about once every 10 years, which would be 23 or 24 in American history.  I was pretty sure not every state had a recall option, so I halved it.  12 felt good.

This is the problem when data leaves out key points....it relies on our own assumptions to fill in the details.  Engineers are normally trained to get explicit with their assumptions when estimating, as evidenced by the famous Fermi problem.  However, even the most carefully thought through assumptions are still guesses.

That's why it's important to remember the quote above: what you're shown is important, but it's not half as interesting as what's hidden.

More on metrics: what about college?

After my post yesterday on metrics, the AVI left a good comment, and then wrote his own follow up post using  sports as an example.  It's worth a read.

I've been thinking more about metrics today, and wondering about other areas where there's no consensus on outcomes.  Before I get in to the rest of my thoughts, I wanted to mention a quick anecdote I once heard a pastor give.

Back when he was in high school, this man's class had been handed a poll.  In it, they were asked what they most wanted to be in life:  rich, successful in their field, famous, successful in love, well traveled or happy.  According to him, when the teacher wrote the results on the board, he was the only one who had put "happy".  As he discussed this with his classmates afterwards, he realized this was because they all had so closely associated happiness with one of the other metrics that it had never occurred to them that checking off "rich" might not be the same thing as checking off "happy".

This occurs to me as a common mistake with metrics....we start associating two traits so closely that we forget they do not actually have to coexist.

This brings me to college.

In the student loan debates, there's been much wailing over how much debt undergraduates are taking on, while the ability to obtain salaries that enable repayment has decreased.  In reading these articles, one would be left with the impression that we had some sort of national consensus on what the point of college actually is: to get a good job.

This is wrong.

According to the Pew Research Center:

Just under half of the public (47%) says the main purpose of a college education is to teach work-related skills and knowledge, while 39% say it is to help a student grow personally and intellectually; the remainder volunteer that both missions are equally important. College graduates place more emphasis on intellectual growth; those who are not college graduates place more emphasis on career preparation.

Even college presidents don't agree on what they're trying to do:

(College) Presidents are evenly divided about the main role colleges play in students’ lives: Half say it is to help them mature and grow intellectually, while 48% say it is to provide skills, knowledge and training to help them succeed in the working world. Most heads of four-year colleges and universities emphasize the former; most heads of two-year and for-profit schools emphasize the latter.

So half of the people heading up colleges never thought that their primary goal would be to get kids good jobs, and 40% of the public didn't prioritize getting a good job.  Loans are generally based on an ability to repay, but a good chunk of those taking out the loans weren't focused on ability to repay when they signed on.

My guess is that this is not what actually went through these people's heads, at least not in those words.  My guess is that maturing and intellectual growth is so conflated with being qualified for a good job that it's unfathomable to some people that they're not the same thing.

Maybe they should start asking this on student loan applications.  I certainly think it should be at least be part of the conversation.

Government benefits OR definitions and the census strike again

Last week I got a little fascinated by the census bureau data.....and this weekend I was sent an article from the Wall Street Journal regarding yet another set of Census Bureau Data that was getting passed around.

This one addressed the number of households in the US receiving "government benefits"....apparently it's up to 49.1%.

Now that's a scary number, but I am always wary of the phrase "government benefits" when it's used in a statistical context.  The problem is that it's an incredibly vague term, and can be used to cover a myriad of programs....not all of which are what initially spring to mind.  

I first learned to be wary of this term when my dear liberal brother mentioned that some group he had been following had claimed that there was some ludicrous number of government handout programs in place today.  The number struck him as high, so he got on their website and found out that they were actually counting both federal assistance programs AND tax breaks (such as home interest deductions, student loan interest deductions, dependent credits, etc) as "entitlements".  Thus in this case I am extra vigilant about my "find the definition" rule.

I took a look around the census website (we've become good friends lately) and found the list they were using as of 2008*:

• Dept of Veteran's Affairs - Compensation, Pension, Education Assistance
• Medicare
• Social Security
• Unemployment
• Workman's Comp
• Food Stamps
• Free/Reduced-Price School Lunch and Breakfast Program
• Housing Assistance
• Federal and State Supplemental Security Income (SSI)
• Medicaid
• Temporary Assistance for Needy Families (TANF)
• Supplemental Nutrition Program for Women, Infants, and Children (WIC)

Not a terribly surprising list, though I wouldn't have realized that Veteran's benefits were on there.  Even without the economy going down hill or any other expansion of programs, the Veteran's benefits most certainly would have expanded in the past few years as people continue

Additionally, it would be important to note that only one member of the household needed to receive this in order to be counted.  That struck me because my parents and my grandmother all live in the same house, which means both of my dear hard working parents are lumped in to that 49.1% number.

Whatever your feeling about government benefits, it's important to know exactly which ones are being counted in any list.  I'd imagine that many people who might dislike Medicaid might not care to eliminate Veteran's Benefits, and those who don't like TANF may very well support workman's comp.  Just something to be aware of, especially in an election year.

*To note: the latest data I could find was from 2008.  I really hate that the WSJ doesn't link to where the heck it got it's numbers.  I couldn't find the stuff they put up anywhere on the census bureau website.  I'm not doubting them, I just wonder if it would have killed them to include a link????