Tag Archives: media

Prince Charles and Princess Diana height situation explained

(With media updates)

They were the same height. More or less.

The most incredibly popular tweet of my life was this:

Many people, assuming I was making some kind of argument about sexism, complained that the tweet was a mountain towering over a molehill, that rules of photographic composition, philatelia, ergonomics, or royal succession somehow required the stamp to be composed this way. In response, I composed the new most incredibly popular tweet of my life:

By then it hit the international press, which apparently has had the same decimation of the reportorial workforce that we’ve had here, so they write articles about tweets where the only background information provided is from other tweets in the thread. So we got:

The last one had this awesome graphic:

stampmistake

The Italian service of Huffington Post even produced the definitive video record of the tweet. Anyways.

Actual facts

The actual facts are that we don’t know exactly how tall they were. Like with popular athletes, the biometric data we have about royalty should be considered suspiciously. At the time of their wedding, in July 1981, everyone saw that they were of similar height, and saw the stamp depicting his head above hers. In response, Buckingham Palace put out a statement announcing that he was an inch taller than her. It was reported in the Stamps column of the New York Times on July 26 like this:

stamp2

To me that seems like a Trumpian lie. “You say I was caught lying, but because of this other untruth my original lie is in essence true.” Making a taller person look even taller seems less egregious than reversing the height advantage. But I don’t know for sure.

The funny thing about resurrecting a 36-year-old scandal is it seems that, among those interested, half nod knowingly and say, “That always annoyed me!” and the other half say, “mind blown.” It’s not just memories, of course the milieu has changed; anger at “masculinity so fragile” that it requires trick photographs has replaced the routine acceptance of trick photography in the service of propriety. And of course the legacy of Diana as unhappy wife to unfaithful creep — and virtual saint — has changed the tone.

Anyway, I’m in the category of people who’ve been talking about this for years:

  • I first raised it in 2010, using the picture of the stamp and others as an example of the taller-man norm: “But the rigid adherence to this norm results in a daily, intimate interaction among almost all couples that reinforces the bigger-stronger/smaller-weaker gender dichotomy.”
  • In 2011, on Sociological Images, Lisa Wade said of the photos: “This effort to make Charles appear taller is a social commitment to the idea that men are taller and women shorter. When our own bodies, and our chosen mates, don’t follow this rule, sometimes we’ll go to great lengths to preserve the illusion.”
  • In 2013 I returned to the issue, this time with data showing that U.S. men and women sort themselves into couples that exacerbate the existing difference in average height between them.

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Finally, I included the stamp picture and the data analysis in my textbook, The Family, writing:

The taller husband conjures up images of the protective, dominant man (“Let me reach that for you”) with a nurturing, supportive wife (“Can I fix you a sandwich?”). To choose a high-profile example, such an image was apparent in many official photos of Britain’s Prince Charles and Princess Diana. Although Charles was actually 1 inch taller than Diana, he often looked shorter than her in candid pictures. But when they posed for portraits, he usually stood on a box or step, as in the picture for the stamp commemorating their royal wedding (Currie 1981). The idea of women as the weaker sex corresponds to the pattern of male domination in modern society, as symbolized by the muscular male athlete and the taller husband.

The reference there is to a news article that uncritically accepted the official heights reported by the authorities. People like to use Google and Wikipedia to find and debate the “official” heights, and to find photos that show them side by side. There may be no true answer.
candd2

This who line of criticism eventually led me to the issue of actual fantasy, in the form of sexual dimorphism in animation. That’s a whole nother tag.

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More bad reporting on texting and driving, and new data

The New York Times‘ problem of misrepresenting the relationship between phones and traffic fatalities, which seems to have begun with Matt Richtel, has just gotten worse.

Richtel sells books on the fear of texting and driving (which, of course, is dangerous), and the website for his book still — despite my repeated entreaties, public and private — leads with the bad, false, unsourced Internet meme, that “the texting-while-driving epidemic continues to claim 11 teen lives per day.” (As a reporter, how could you sleep one night with that BS up under your name? Mind boggling.)

Anyway, the new entrant is David Leohnardt. At the heavy risk of jeopardizing future opportunities to publish on the Times op-ed page, I tweeted that his recent column included “one of the dumbest things I’ve ever read in the NYTimes.” Washington Post WonkBlog writer Jeff Guo pointed out Leonardt’s column, which claimed that, with regard to the recent spike in traffic deaths, “The only plausible cause is the texting, calling, watching, and posting that people now do while operating a large piece of machinery.” The column contained not a piece of evidence to support that claim (though there were some awful anecdotes), which is why I said it was dumb.

Which is too bad. But even though the spike in traffic deaths is concerning, reporting should not be wrong.

Early estimates from the National Safety Council (which uses a different method than the Federal NHTSA) show a 6% increase in traffic fatalities for 2016. Leonhardt, working really hard to make that absolutely as alarming as possible, produced this graph, showing percent change in fatalities over successive two year periods going back to 1980:

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Because it’s hard to add up the pluses and minuses in your head, It would be really easy — really really easy — to look at Leonhardt’s chart and think fatalities are higher now than they were in 1980. But rather than pointing out that fatalities per person have fallen by half since 1980, he instead writes, “It’s the first significant rise in a half century,” which would be true except for the significant rise in every single decade of the last half century.

This is a lot like when Richtel described the 2015 rise as, “soaring at a rate not seen in 50 years.” Not that the rate was not seen in 50 years, of course, just that the soaring of the rate hadn’t been (or so the NYT Science Desk told me when I complained).

Adding 6% to the NHTSA numbers for 2015, I get the follow graph, showing the trends in deaths per person in the population, and deaths per mile traveled, as changes since 1970. (The deaths per mile haven’t been released for the whole year yet; click to enlarge.)

PercentWhite

That is a troubling spike, which takes us all the way back to 2009 fatality rates. We should make the roads safer, by using them less and using them more safely. But come on, NYTimes.

Read the whole, completely aggravating series, under the texting tag.

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Breaking: Trump has terrible judgment

Say what you want about his decrepit values, noxious personality, and authoritarian political views, but we should all be able to agree Trump has terrible judgment. Also that he doesn’t care about little people. And a lot of people who like him are deplorable.

This time, the story behind the story.

On Monday night Trump pulled himself away from MLK reverie long enough to notice that CNN was doing a show about his daughter, Ivanka. He saw someone praising her on Twitter and copied his message. He wrote:

djtgoodspine

The Daily News captured the original tweet, by Lawrence Goodstein (drgoodspine) revealing that Trump had lowercased “Great” and added a comma after it, but failed to notice that the good Dr. Goodstein got Ivanka’s Twitter handle wrong.

drgoodspine

Hilarity ensued, and the story focused on how the real @Ivanka responded by telling him to pay attention to climate change.

I haven’t seen any media focus on Goodstein, apparently because he deleted his account right away. But I happened to notice it in time, and screen-grabbed a few tweets. The point of my showing them is: Trump has no idea what he’s doing or how it affects real (little) people, and doesn’t care anyway. Secondarily, the guy is awful and any reasonable public figure would want nothing to do with him – at least as he represented himself on Twitter – and certainly wouldn’t give him a platform of millions on Twitter. (I didn’t notice how many followers Goodstein had, but I remember thinking it wasn’t many.)

I didn’t save all of his tweets, but I got a few that I considered representative, because it was immediately apparent that a lot of what he did on Twitter was call people assholes, including President Obama, “Norm” Chomsky, and a lot of journalists, often by juxtaposing their face with a picture of an asshole. Take a look (click to view individual images):

 

Who cares? I don’t care about Goodstein. He claims to have spent a year treating 9/11 victims in New York, and for all I know he’s a good chiropractor. So he loves Trump – not surprising given what an unpleasant person he seems to be. The point is about Trump’s bad behavior. Some Trump fans live for a retweet from the great Tiny Hands. Maybe Goodstein did, too. But he apparently wasn’t really prepared for that big of a spotlight to shine on his nasty asshole-screaming habit (or maybe he was fine with it and it was a Trump goon squad that made him shut it down to prevent embarrassment – to Trump.)

And who shouts to millions of people without the slightest consideration of the context and content of what they’re shouting? Trump has had worse tweets, and done many much worse things, but his platform is actually still growing, and the power he has is increasing. He should not treat individuals like this. Before he turns someone’s life inside out, someone should check it out. Can the person handle it? Do they want to? Obama has had some wonderful moments with random citizens, but I don’t think they started with him landing Marine 1 on their lawn with the press pool and no advance people.

Finally, there are potential security implications, obviously, when a president acts so impulsively. One thing to notice is that Goodstein’s handle, @drgoodspine, was snapped up by someone, and they now have a potentially damaging platform as well, as Trump’s tweet is still out there.

Anyway, I just wrote this to help keep the record of bad judgment complete, seeing that no one was reporting it.

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No paper, no news (#NoPaperNoNews)

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In the abstract, the missions of science and science reporting align. But in the market arena they both have incentives to cheat, stretch, and rush. Members of the two groups sometimes have joint interests in pumping up research findings. Reporters feel pressure to get scoops on cutting edge research, research that they want to appear important as well as true — so they may want to avoid a pack of whining, jealous tweed-wearers seen as more hindrance than help. And researchers (and their press offices) want to get splashy, positive coverage of their discoveries that isn’t bogged down by the objections of all those whining, jealous tweed-wearers either.

Despite some bad incentives, the alliance between good researchers and good reporters may be growing stronger these days, with the potential to help stem the daily tide of ridiculous stories. Partly due to social media interaction, it’s become easier for researchers to ping reporters directly about their research, or about a problem with a story; and it’s become easier for reporters to find and contact researchers to cover their work, and for comment or analysis of research they’re covering. The result is an increase in research reporting that is skeptical and exploratory rather than just exuberant or exaggerated. Some of this rapid interaction between experts researchers and expert reporters, in fact, operates as a layer of improved peer review, subjecting potentially important research to more extreme vetting at just the right moment.

Those of us in these relationships who want to do the right thing really do need each other. And one way to help is to encourage the development of prosocial norms and best practices. To that end, I think we should agree on a No Paper No News pact. Let’s pledge:

  • If you are a researcher, or university press office, and you want your research covered, free up the paper — and insist that news coverage link to it. Make the journal open a copy, or post a preprint somewhere like SocArXiv.
  • If you are a reporter or editor, and you want to cover new research, insist that the researcher, university, or journal, provide open access to its content — then link to it.
  • If you are a consumer of science or research reporting, and you want to evaluate news coverage, look for a clear link to an open access copy of the paper. If you don’t see one, flag it with the #NoPaperNoNews tag, and pressure the news/research collaborators to comply with this basic best practice.

This is not an extremist approach. I’m not saying we must require complete open access to all research (something I would like to see, of course). And this is not dissing the peer review process, which, although seriously flawed in its application, is basically a good idea. But peer review is nothing like a guarantee that research is good, and it’s even less a guarantee that research as translated through a news release and then a reporter and an editor is reliable and responsible. #NoPaperNoNews recognizes that when research enters the public arena through the news media, it may become important in unanticipated ways, and it may be subject to more irresponsible uses, misunderstandings, and exploitation. Providing direct access to the research product itself makes it possible for concerned people to get involved and speak up if something is going wrong. It also enhances the positive impact of the research reporting, which is great when the research is good.

Plenty of reporters, editors, researchers, and universities practice some version of this, but it’s inconsistent. For example, the American Sociological Association currently has a news release up about a paper in the American Sociological Review, by Paula England,  Jonathan Bearak, Michelle Budig, and Melissa Hodges. And, as is now usually the case, that paper was selected by the ASR editors to be the freebie of the month, so it’s freely available. But the news release (which also only lists England as an author) doesn’t link to the paper. Some news reports link to the free copy but some don’t. ASA could easily add boilerplate language to their news releases, firmly suggesting that coverage link to the original paper, which is freely available.

Some publishers support this kind of approach, laying out free copies of breaking news research. But some don’t. In those cases, reporters and researchers can work together to make preprint versions available. In the social sciences, you can easily and immediately put a preprint on SocArXiv and add the link to the news report (to see which version you are free to post — pre-review, post-review, pre-edit, post-edit, etc. — consult your author agreement or look up the journal in the Sherpa/Romeo database.)

This practice is easy to enforce because it’s simple and technologically easy. When a New York Times reporter says, “I’d love to cover this research. Just tell me where I can link to the paper,” most researchers, universities, and publishers will jump to accommodate them. The only people who will want to block it are bad actors: people who don’t want their research scrutinized, reporters who don’t want to be double-checked, publishers who prioritize income over the public good.

#NoPaperNoNews

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Gender on the Diane Rehm show in September

The last Media Matters report on the Sunday TV talk shows reported that 73% of guests were men in 2015, a little less than the 75% recorded for the previous two years. (That includes journalists as well as politicos.) I expect my local NPR station, with its liberal audience, to have a better showing for women, and it does. The Diane Rehm Show, which is produced at WAMU but distributed nationally as well as podcasted, had 129 guests in September, and 80 of them (62%) were men, by my manual count. (I’m not counting the hosts, who changed over the month.)

But what has been striking me lately, and the reason I did the count, was how rarely it seems that women are in the majority among the guests, and especially how often there is one woman and more than one man. Without a whole conversation analysis, you can imagine the kind of dynamic that made me think, “sure is a high male/female word-count ratio in this discussion.”

The count confirms this. The show averaged 2.8 guests per episode. So how are the men and women distributed? Of the 46 shows aired in September, 12 featured just one guest, 8 of whom were male. Male guests outnumbered female guests overall in 29 episodes, or 63% of the shows. Female guests outnumbered men in only 8 shows (17%), with the remaining 9 (20%) being gender balanced. What accounts for my annoyance, maybe, was that in those male-dominated shows, more than half (16 of 29) featured just one woman and more than one man. The reverse – one man and more than one woman – happened just three times. Details in the figure.

dianerehmgender

The most common configuration is one woman and two men. 

My point is just that a 62% / 38% gender split leads to a lot of small-group discussions where men outnumber women, and especially solo-women versus multiple men, which is its own kind of gender situation. I imagine you get this pretty often in cases – say, at an academic conference – where there is some effort to reach gender balance on most panels, but women are less than half altogether. (You can see they were paying attention because there were no all-male panels of four or five.)

I’ll leave it to Media Matters to do their annual report again next year, but I did take a quick look at some of the Sunday shows for September. On Meet the Press I found 62% men, and 75% of the shows were male-dominated. On Fox News Sunday 71% of guests were male, and every show was male-dominated. Face the Nation had 72% male guests but also every one male-dominated. (Incidentally, Face the Nation has a convenient list of every guest so far for the year, so I was able quickly tally the gender of their 348 guests, 73% of whom were men, counting multiple appearances. That’s a tiny bit better than their 2015 total of 76%.)


Related on gender composition:

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The fathers behind teen births (or, statistical memes and motivated blind trust)

When makes people trust statistical memes? I don’t know of any research on this, but it looks like the recipe includes a combination of scientific-sounding specificity, good graphics, a source that looks credible, and – of course – a number that supports what people already believe (and want their Facebook friends to believe, too).

If that’s the problem, and assuming the market can’t figure out how to make journalism work, I have no solution except seizing the Internet and putting it under control of the Minister of Sociology, or, barring that, encouraging social scientists to get engaged, help reporters, and make all their good work available publicly, free, and fast.

Today’s cringe:

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The blogger TeenMomNYC takes credit for creating this, and the Facebook version has been shared tens of thousands of times. Its popularity led to this story from Attn: “The Truth About Teenage ‘Baby Mamas’ is Quite Revealing.” (If anyone did want to study this issue, this is a neat case study, because she posted 8 “did you know” graphics on Facebook at the same time, and none of the others took off at all – why?)

I don’t know anything about TeenMomNYC, but I share her desire to stop stigmatizing and shaming young mothers. I wish her work were not necessary, but I applaud the effort. That said, I don’t necessarily think shaming young fathers (even if they’re not quite as young) is a solution to that, but that’s not the point. My point is, what is this statistic?

According to the footnote (thanks!), it comes from this 1995 National Academies report, and (except for changing “29” to “29.7”) it represents it accurately. From p. 205:

These data highlight an additional component of the sexual abuse picture— the evidence that an appreciable portion of the sexual relationships and resulting pregnancies of young adolescent girls are with older males, not peers. For example, using 1988 data from the NSFG and The Alan Guttmacher Institute, Glei (1994) has estimated that among girls who were mothers by the age of 15, 39 percent of the fathers were ages 20–29; for girls who had given birth to a child by age 17, the comparable figure was 53 percent. Although there are no data to measure what portion of such relationships include sexual coercion or violence, the significant age difference suggests an unequal power balance between the parties, which in turn could set the stage for less than voluntary sexual activity. As was recently said at a public meeting on teen pregnancy, “can you really call an unsupervised outing between a 13-year-old girl and a 24-year-old man a ‘date’?”

This is an important point, and was good information in 1995, when it cited a 1994 analysis of 1988 data, which asked women ages 15-44 a retrospective question. In other words, this refers to births that took place as early as 1958, or between 28 and 58 years ago. That is historical, and really shouldn’t be used like this today, given how much has changed regarding teen births.

The analysis is of the 1988 National Survey of Family Growth, a survey that was repeated as recently as 2011-2013. Someone who knows how to use NSFG should figure out the current state of the age gap between young mothers and fathers and let TeenMomNYC know.

Even if I didn’t know the true, current statistic, this would give me pause. Births to women before age 15 are extremely rare. The American Community Survey, which asks millions of women whether they have had a birth in the previous year, does not even ask the question of women younger than 15. The ACS reports there were 179,000 births in the previous year among women who were under 20 when interviewed, of which only 6,500 were to women age 15 at the interview. So that’s 3.7% of teen births, and 3 out of every thousand 15-year-old women. In 1958 this was much more common, and the social environment was much different.

Another issue is the age range of the fathers, 20-29, which is very wide when dealing with such young mothers. Look at the next phrase from the 1995 report: “girls who had given birth to a child by age 17, the comparable figure was 53 percent.” Realize that the great majority of girls who had a birth “by age 17” were 17 when they did, and the great majority of those men were probably close to 20. I’m not very positive about 20-year-old men having children with 17-year-old women, but it’s pretty different from 29-versus-13.

I can’t find the original source for this, but this report from the Resource Center for Adolescent Pregnancy Protection attributes this table to the California Center for Health Statistics in 2002, which shows that the father was age 20 or older  for 23% of women who had a birth before age 15. And of those, 93% were 20-24 (rather than 25+).

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Anyway, this is a good case of a well-intentioned but under-resourced effort to sway people with true information, picked up by click-bait media and repeated because people think it will help them win arguments, not because they have any real reason to believe it’s true (or not true).

So I really hope someone with the resources, skills, and training to answer this question will produce the real numbers regarding father’s age for teen births, and post them, with accompanying non-technical language, along with their code, on the Open Science Framework (or other open-access repository).

Fixing the media and its economy is a tall order, but academics can do better if we put our energy into this work, reward it, and restructure our own system so that good information gets out better, faster and more reliably.

Related posts:

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Black women really do have high college enrollment rates (at age 25+)

The other day I reported on the completely incorrect meme that Black women are the “most educated group” in the U.S. That was a simple misreading of a percentage term on an old table of degree attainment, which was picked up by dozens of news-repeater websites. Too many writers/copiers and editors/selectors don’t know how to read or interpret social statistics, so this kind of thing happens when the story is just too good to pass up.

I ignored another part of those stories, which was the claim that Black women have the highest college enrollment rates, too. This is more complicated, and the repeated misrepresentation is more understandable.

Asha Parker in Salon wrote:

By both race and gender there is a higher percentage of black women (9.7 percent) enrolled in college than any other group including Asian women (8.7 percent), white women (7.1 percent) and white men (6.1 percent), according to the 2011 U.S. Census Bureau.

You know the rewrite journalists are playing telephone when they all cite the same out-of-date statistics. (That Census report comes out every year — here’s the 2014 version; pro-tip: with government reports, try changing the year in the URL as a shortcut to the latest version.)

But is that true? Sort of. Here I have to blame the Census Bureau a little, because on that table they do show those numbers, but what they don’t say is that 9.7% (in the case of Black women) is the percentage of all Black “women” age 3 or older who are attending college. On that same table you can see that about 2% of Black “women” are attending nursery school or kindergarten; more relevant, probably, is the attendance rate for those ages 3-4, which is 59%.

So it’s sort of true. Particularly odd on that table is the low overall college attendance rate of Asian women, who are far and away the most likely to go to college at the “traditional” college ages of 18-24. That’s because they are disproportionately over age 25 (partly because many have immigrated as adults). But, if you just limit the population to those ages 18-54, Black women still have the highest enrollment rates: 15.5%, compared with 14.6% for Asians, 12.6% for Hispanics, and 12.4% for Whites. Asians are just the most likely to be over 25 and not attending college, most of them having graduated college already.

This does not diminish the importance of high enrollment rates for Black women, which are real — after age 25; the pattern is interesting and important. Here it is:

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Under age 25, Black women are the least likely to be in college, over 25 they’re the most likely. This really may say something about Black women’s resilience and determination, but it is not a feel-good story of barriers overcome and opportunity achieved. And, despite her presence in the videos and stories illustrating this meme, it is not the story of Michelle Obama, who had a law degree from Harvard at age 24.

This is part of a pattern in which family events are arrayed differently across the life course for different race/ethnic groups, and the White standard is often mistaken as universal. I have noted this before with regard to marriage (with more Black women marrying at later ages) and infant mortality (which Black women facing the lowest risk of infant death when they have children young). It’s worth looking at more systematically.

ADDENDUM 6/29/2016: Cumulative projected years of higher education

If you take the proportion of women enrolled in each age group, multiply it by the years if the age group (so, for example, 18-19 is two years), and sum up those products, you can get a projected total years in college (including graduate school) for each group of women. It looks like this:

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Note this makes the unreasonable assumption that everyone who says they are enrolled in college in an October survey attends college for a full year. So, for example, Asian women are projected to spend 6.2 years in college on average between ages 18 and 54. What’s interesting here is that Black women are projected to spend more years in higher education than White women (5.5 versus 4.9). But we know they are much less likely than White women to end up with a bachelor’s degree (currently 23% versus 33%). This has to be some combination of Black women not spending full years in college, not going to school full time, or not completing bachelor’s degrees after however many years in school. Attendance may be an indicator of resilience or determination, but it’s not as good an indicator of success.

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