This could be me.
Our country’s checks and balances are based primarily on the independence of the three branches of government: executive (President), legislative (Congress) and judicial (Supreme Court). The separation of federal and state government is another way, but that’s not my focus. I got to wondering how representative the U.S. Supreme Court is of the country as a whole. The responsibility of interpreting the U.S. Constitution and statues involves value judgments: how much process is “due”; what legislation is “appropriate?” These and many other words in the Constitution are very subjective.
Of course the judicial branch is not supposed to be subject to the vagaries and political pressures of the election process, but it is still arguable that the entire country’s legal system ought not to be ruled by an elite few with a restricted, insular view of such values. Therefore I researched where every Supreme Court justice grew up and where they received their legal education. I limited my review to those who served within the last 100 years, after the “lower 48” were all states. Consider these maps:
The numbers show how many justices grew up or were educated in those states. There were a total of 56 researched. Some justices moved throughout their youth, but I did my best to identify the state for which they would considered a “native son” or “native daughter,” usually where they lived during middle and high school years which I consider formative. The second map generally shows where they attended law school, but many justices in the earliest part of the range never graduated from law school and may not ever have attended law school. “Reading the law” with a law firm or judge and then taking the bar was a common method of obtaining a legal education up until the 1960s or so. The maps do not necessarily reflect where the justices practiced law, which did include some states not shown as represented (such as Wyoming).
The northeast is heavily represented, some may say over-represented, especially in the second map. Almost all of the those educated in Massachusetts, Connecticut, New York, or New Jersey were from Ivy League law schools (Harvard, Yale, Columbia, and Princeton respectively). The Midwest gets some fairly decent representation at least on the top map, but the Deep South and West seem to be short-changed. Some very populous states, such as Florida and North Carolina, have not had a justice appointed in the last 100 years, and Texas has had only one. This trend toward the Ivy League has gotten stronger in recent years, which seems surprising considering the push for diversity in other parts of government. The last justice to serve who didn’t attend an Ivy League law school was Sandra Day O’Connor (appointed in 1981). Kentucky surprised me, but it was probably an important swing state between the north and south in the early 20th century and I suspect politics played a part in those appointments. The most recent Kentuckyan to serve was Chief Justice Fred Vinson (1937 – 1943). Many of the justices were politicians before their appointments and quite a few came from very modest circumstances, although most were from relatively prosperous, well-educated families.
I’m taking a Python class at the local Adult Ed. They just had us code a fractal snowflake to teach us recursion. It’s kinda fun, I suppose.
My code is below:
import turtle def koch(t, length, n): if n == 0: return angle = 60 t.fd(length*n) t.lt(angle) koch(t, length, n-1) t.rt(2*angle) koch(t, length, n-1) t.lt(angle) t.fd(length*n) def snowflake(t,length,n): for i in range(6): koch(t, length,n) t.rt(60) myrtel = turtle.Turtle() snowflake(myrtel, 3, 5) turtle.mainloop()
I really tried to like this one, but just couldn’t. April May is a 20-ish bisexual artist/designer in New York. She happens upon a massive Transformer-like sculpture on the sidewalk one night and calls her friend Andy to come make a video. The robot, which she names Carl, appears simultaneously all over the globe in big cities. An advertising gimmick? Alien? Art? April becomes famous and her life goes to hell. The book was billed as science fiction but it’s more of a fantasy. There was little science in it and what there was did not make the plot even slightly plausible. It seems to be mostly about personal relationships and how people screw them up. Reviewers have called it witty but that’s lost on me. I just found it weird.
I just uploaded a new cryptic crossword. To play, click on the link, not the picture.
You may be aware that for quite some time, the overall birth rate in the U.S. has been dropping. However, some states are making a comeback in this regard. The following map shows which states’ birth rates are rising or falling the fastest. It covers the period 2010 to 2016. Note that the states shown as High do not necessarily have high birth rates; rather they have the highest increase in their birth rate compared to other states. Similarly, Low means the decrease in rate is greatest there, but it may still be relatively high. The changes may be due to migration, immigration, a changing demographic (e.g. young/old or ethnicity), or economic factors among other reasons. In general, though, an increase signifies an increased vitality in a state or at the very least, a lessening of a pessimism or depression that may have existed. The zero change point is between Colorado and Oregon. Darker green means positive change in birth rate, while the paler the green or yellow, the more the birth rate has dropped.
The increase for North Dakota was just over 25%, and for D.C. about 7.5%. The decrease for New Mexico was about 11% and Vermont 7.5%. All the other states were in the range from -7% to +4.8%.
The authors give an account of their three-year journey by small plane across America, telling us their impressions of the communities they visited. The focus is on one question: why here? The question applies both to the residents and to the businesses that provide the economic lifeblood. Since the book avoids the major metropolitan areas, one answer universal to all the locations in the book is the low cost of being there. Low cost of living and low cost of labor make a town attractive to families and employers alike. But since that applies to probably 90% of the geographic area of America, I was looking for more – for what makes a town unique – i.e. what makes a town thrive “in the sticks?”
The authors do give many interesting tidbits along those lines, and that made the book worth reading. I’ll mention a few in a bit, but since they tend to be spoilers, I want to save those until later. I was sorely disappointed in a couple of aspects of the book, however. First and foremost is the fact that the title is a bait-and-switch. The authors wrote very little about towns. The vast majority was about medium-sized cities. Of the 29 listed names in the Table of Contents, the median population was 47,000. Two of them were state capitals and others were major regional hubs. There were only three towns below population 3000 and anything below population 20,000 got very short shrift, mostly no more than two pages. The other disappointment was the repetition. Nearly every chapter focused on just a few aspects of these cities: civic boosterism, (re)vitalization of the downtown, K-12 education, libraries, brewpubs, and river walks. These things are important, to be sure, but differed very little in their specifics and didn’t tell us much we didn’t know since virtually every town does the same thing. I skimmed a lot through the second half of the book.
Now for some of the spoilers, but they’re reasons why you should read the book. On the plus side, one unexpected bonus was the description of what it’s like to tour the country by small plane. I learned a lot that I didn’t know or hadn’t thought about, such as what makes a small regional airport good (clean bathrooms, a good crew car, a good-sized runway). The best parts for me were the accounts of a local lifeblood enterprise. Most were major businesses but these also included military bases, universities, or unique geographical features. An obvious one that attracts employers is proximity to major road, rail, or water routes, but some are not so obvious: a windswept plain that attracts windmill manufacturers; a midwestern town where the residents speak clear, “unaccented” American English that’s perfect for call centers; an abandoned factory or closed military base that already has valuable infrastructure. Often the key was simply the value of being a hometown for someone who made it big. One lesson I learned was how much people have an affection for where they grew up, so inventors and entrepreneurs, even actors or sports stars, return there and set up shop, providing jobs.
Consider this map:
The many solid blue or solid red states are an indication of the polarization that has occurred in our country in recent years, and I believe it’s unfortunate. However, the states with colors in between are proof that candidates of both parties can be elected there. It was compiled in the following way. I gave one point each for Republican office holders in the position of U.S. Senator or Governor, one point for those states that went for Trump in 2016 and one point for each quartile of the state’s GOP Congresspersons. In other words, if the state had 75% or more of its representatives Republican, it got three points; if 50% or more, 2; 25% or more, 1; and less, 0. Thus a state could get from 0 to 8 “redness” points. Of course even the deep blue or deep red states might have some Congresspersons of the opposite party, just fewer than 25%. It also doesn’t take into account mayors, state officeholders, or voter registration, so it’s by no means definitive. There are also a couple of elected Independents in the mix. I am both surprised and dismayed at how few states are in the middle, only two purple states and three light blue.
I do not contend that this is good or bad, nor is it likely to predict anything for the 2020 national elections. Students of political science would be well-advised to consider the effect of demographics on this type of map. States in the red category especially, such as Florida, for example, may not be as red as they look for purposes of a presidential election. Democratic voters tend to be concentrated heavily in small areas such as major cities. 700,000 Democrats in an inner city district may elect one congressperson, while 700,000 Republicans spread in suburban or rural areas might elect two, but in a presidential election, the vote is split 50-50. Gerrymandering tends to accentuate this even more.
One more post about baby names and then I’ll leave it.
As with other reviewers, this charming story is a childhood favorite of mine. David is a boy of ten or so who has just moved into a new house at the foot of a mountain. He explores the mountain and discovers The Phoenix, a huge talking bird who is vain, pretentious, and adventure-loving. He and David become fast friends. Since it’s summer vacation David spends every day climbing the mountain and going on adventures with the Phoenix. They meet a witch, gryffens, a faun, and other mythical creatures. The book has very much the same feel as the song Puff the Magic Dragon by Peter, Paul, and Mary. The Phoenix is being pursued by The Scientist, who, unfortunately, is not given a sympathetic treatment. The book was a Weekly Reader Children’s Book Club selection. Although aimed at children, the vocabulary is surprisingly advanced. It would make an excellent read for or to a child of David’s age. At some point I must have mentioned this book to my wife, as she obtained a copy from the local school district some time in the past and was able to locate it on our shelves when I remarked about it. I owned a copy as a child, but that one is long gone and this one is not it. It’s probably not available in your local library, but it is at Amazon in both Kindle and hard cover versions.
In my last post I discussed recent trends in baby names, focusing on why some have come into or gone out of fashion. Today I want to look at which names are regional, and speculate why that is. These tables might be useful for authors choosing names for their characters. I selected several boys’ and girls’ names that show marked regional preferences. See the table:
|Name||Sex||Region||States where most popular|
|Isaac||M||Mormon||UT, NV, AZ|
|Clyde||M||Appalachia||WV, TN, NC, KY|
|Anthony||M||Italian||NY, NJ, RI|
|Lars||M||Scandinavian||WA, MN, CA|
|Horace||M||South||GA, AL, SC|
|Clifton||M||Deep South||MS, NC, VA, LA|
|Noel||M||Big population states||TX, CA, NY|
The ethnic names are pretty easy to analyze for regional preferences. Similarly, Old Testament names are very popular among Mormons both for boys and girls. The other names show the regional preferences in the chart, but I’m not sure why. Clifton is an English name. It’s not very popular these days, but historically, it’s been a southern name for some reason. I remember the old song Wolverton Mountain and its fearsome character Clifton Clowers, which was set in Arkansas. I never thought of Horace as a southern name, but it clearly is one. Of course it’s the name of a Roman poet. The name Clyde is Scottish and that can probably explain why it’s popular in Appalachia where Scots-Irish settled heavily in early America, probably due to their mining experience. I have a pretty good idea why Noel is markedly more popular in the states with big populations. See notes of methodology below. The list of states in the table, by the way, are in the order of how popular the names are (or were, since the data covers from 1910 to 2017). Most of the regional preferences have moderated in recent decades, presumably due to travel being easier now and populations mix more.
Now for the girls.
|Name||Sex||Region||States where most popular|
|Gretchen||F||German/Scandinavian||MN, IA, WI|
|Madonna||F||Upper Midwest||IA, IN, SD|
|Aliyah||F||Arab? Spanish?||NV, AZ, FL|
|Dolly||F||Appalachia||WV, KY, VA|
|Elaine/Elena||F||Elaine: Northern Half, Elena: SW||Elaine: evenly distributed, Elena: NM, AZ, CA, TX|
|Annie||F||Deep South||AL, MS, GA, SC, NC|
|Latoya||F||African-American||DC, MS, LA|
Gretchen and Latoya can pretty much be explained by ethnicity. I haven’t identified a reason for Madonna’s and Dolly’s regional trends. Aliyah is very popular among Arabs according to websites I visited, yet its preference is in largely Hispanic states. It must also be popular among Spanish speakers. Most surprising of all for me, however, was Annie. That name has a very pronounced popularity in the Deep South compared to the rest of the country, the most extreme regionality of any of the names I found, yet I was not aware it was a southern name. It was popular throughout all the South. Similarly Elaine was popular throughout the northern half rather evenly distributed, yet not at all in the South. Elena can perhaps be explained as a Spanish name, but I thought it was curious how these two near-identical names split the country on a north-south basis.
I tried to find non-ethnic names that showed regional preference, in some of the other areas, like the West, Florida, etc. My own name, Russ, does prefer the Northwest: WA, OR, CA; but it wasn’t as stark a difference as the names in the charts. Constance was strongly regional to New England (ME, RI, NH) up through the 1950s, but is rare now and evenly distributed.
A note on methodology. The data is from the U.S. Census, which releases baby names for every state every year. My data covers 1910 – 2017. The popularity numbers are based on percentage of babies with the name, not the count. Because the U.S. Census Bureau for privacy reasons only publishes the names which occurred five or more times in a year in each state I had to adjust the percentages. I was able to obtain the total number of babies (names not listed) born in each state each year and by comparing the totals of named babies to total babies I could determine accurate percentages for babies whose names appeared in all states. For less common names where some years they didn’t appear five times or more in some or all states, I have no data, or only data from populous states and those rankings are not accurate. That probably explains Noel. I found it surprising that in some states some years over half the babies born did not make the five minimum cutoff. Bear in mind, too, that the popularity varied over time and may not be accurate for the current day.
Recent trends in baby names can only be tracked through 2017 since U.S. Census data has published only that far. There are some interesting trends, though. If you just want to know what’s popular these days, you can go to the census site. I’m more interested in what has changed significantly upward or downward and why. Take a look at these charts for the male names Theodore and Colby.
I’m not sure why Colby (and its variant Kolby) first became moderately popular in the 1970s, but the spectacular jump in 2001 I traced to the success of a contestant on the TV show Survivor at that time. The name hasn’t surfaced in pop culture since then that I could find, which is no doubt why it has subsided since then. Theodore, of course, was first popular when our president bore that name. It’s not clear to me why a gradual resurgence began around 2010. Although it’s gradual, it’s quite substantial. Such a slow climb is not typical of a pop culture cause, and is rare among traditional names such as Theodore. The name Winston has a somewhat similar resurgence, beginning about that same time. Is there a new interest in historical figures?
Now let’s examine girl’s names.
Girl’s names tend to be more influenced by pop culture than boy’s names. Jolene (1973) was Dolly Parton’s most popular song in terms of how often it was recorded by others. She also did a popular cover with the band Pentatonix in 2016, no doubt accounting for the surge then. I’m having more trouble attributing those spikes in Samara’s profile. Actress Samara Weaving might be the cause of the most recent one since she’s had major roles in recent movies and the TV series SMILF, but I haven’t been able to track down anything for 2003 where it first jumped. I examined where the name Jolene was most popular during these different time frames. Prior to 1973 the three states in which the name was most popular were Utah, Iowa, and Nebraska. During 1973 – 1977 it was the Dakotas and Alaska (country music territory), and after 2010, West Virginia, Ohio, and Missouri (also country music territory). It may be possible to track demographic movements this way. Much has been written recently about the steroid “crisis” centered on West Virginians moving into Ohio. See my review of Hillbilly Elegy as a good example.
Oddly, or perhaps not, negative publicity about a name, such as an assassin, child molester, or despicable TV character does not seem to result in a precipitous drop in a name’s popularity. Some names do drop, though, and it’s seldom clear why. Colby is perhaps the exception, but it’s clearly not due to negativity, only the absence of the preexisting media boost. Why do long-popular names drop?
I just noticed that my prior post with a link to my very first YouTube video is not working, so I’m reposting the YouTube link. The song is Candy Man.
It’s difficult to put a star rating on this one. It’s written in the first person through the eyes of a severely autistic English boy (Christopher) who is also a math whiz. Or maths as they say over there. As such, the language is stilted and simplistic. The “plot,” which Christopher considers to be a mystery, is nothing more than a recounting of his experiences involving a neighbor’s dog who was killed and his own broken home.
I have a severely autistic nephew and I’m very sympathetic to the author’s attempt at bringing understanding to the public of how autistic children think and feel. However, I can’t say I liked the book. I feel almost guilty that I don’t like it better, but the language was boring and, frankly, not very realistic in my experience. I understand the author has extensive experience with autistic children, so perhaps he knows some who speak and act like Christopher, but my nephew is less gifted and more normal. He is a great bowler, though. He once bowled a 300 game. I didn’t hate the book, but I did find myself skipping over a lot of it, especially the digressions where Christopher explains ordinary things. I understand better now how women feel about mansplaining.
Now that the Chinese have put a lander (the Chang’e-4) on the far side of the moon, news announcers all over America have been saying it landed on the dark side of the moon. Wrong! The far side gets just as much sunlight as the near side. When the moon is full the far side is dark but when it’s a new moon, the far side is in full sunlight. Is it any wonder American kids are so bad at science when authority figures put out bad science?
Semiosis is a science fiction book about the colonization of a distant planet by humans – pilgrims of a sort. I gave up on it after about 60 or 70 pages, so I’m not posting an actual review or a star rating. I didn’t give it enough of a chance to judge its real merit, but I thought it would be useful to some readers to know that it starts slow and drags from there. It is rather depressing at the beginning, too, but there’s reason to see hope based on reviews and promotional blurbs. If you’re into world-building sci-fi, you may like it.
I haven’t had much to blog about the last few days but I felt I should at least welcome 2019 in with a post. I wish all my readers a happy 2019. For Christmas I got myself a new laptop and some UnderArmour running pants. My kids gave me a combination crossword-jigsaw puzzle. and a book on breaking codes with Python. I’ve already solved the crossword part and now I’m using the finished crossword as a guide to complete the jigsaw. That’s it for now. Stay safe.
I’d call this vintage Tom Clancy except it’s very current, not vintage. It is, however, true to form: lots of combat at all levels – hand-to-hand, small arms, and military force. The story involves the doings of both Russian and western spy agencies in Ukraine during the period of Russia’s takeover of the Crimea, threatening to move on Kiev. That story line stars Jack Ryan, Jr., son of President Jack Ryan. At the same time there is a back story starring Jack Sr. when he was a CIA analyst. The chapters switch back and forth in time. Major players are the Russian FSB and a fictional(?) organized crime syndicate called the Seven Strong Men as well as the CIA and British IO’s. The combat scenes are detailed and very credible as Clancy shows his encyclopedic knowledge of armaments and tactics. The political side is also more sophisticated and at least a bit more nuanced than some of his early books. Like those, this one is too long, but sometimes that can be good, especially if you’re listening on a long drive. Clancy’s writing style has improved, too, or perhaps he’s gotten better editors. I can give it a solid three and a half stars.
I listened to the audiobook (14 disks). It was narrated by Lou Diamond Phillips (Henry from the Longmire series), who did an excellent job.
A woman sees her own photo in an advertisement in the personals section of the newspaper along with a phone number. It’s a non-working number. She is disturbed because it would appear to others that she is a prostitute. It turns out there are more women to whom this happens. Then we learn that some are victims of rape or murder. The police are slow to accept this as a serial crime and there is rivalry between the meek transit policewoman and the tough homicide cop running the main investigation. I can’t give this a strong recommendation as the ending was too predictable and the evil character running the mysterious “Find the One” website was overdone. The dynamics between the officers seems very artificial, too. Up until the end, though, it was engaging enough and kept me interested, so I can give it three stars. I listened to the audiobook and the reader was good.
The above chart shows the relationship between my relatives and their physical distance from me. If you read my preceding post you’ll see that 23andMe provides a map showing the location of one’s DNA relatives (for those who have shared that information). That made me wonder how far (or close) people people generally move or settle in relation to their family.
I’ve lived in several cities around the country including Seattle and New York, and even Tokyo, Japan for my senior year abroad, but I ended up settling for my adult life about eight miles from where I grew up in the San Jose area. In the above chart, degree 1 includes my closest relatives, i.e. those people who share 50% of my DNA, which is my children, siblings, and parents. Degree 2 is those with 25%, such as grandparents, aunts, uncles, nieces, nephews. Using my own genealogical information and family knowledge, along with a few Google searches, I was able to go out as far as some second cousins (Degree 5). The 6th level shown is taken from that 23andMe map. I used all the 3rd cousins I could find on that map, and no doubt that relationship is only estimated based on shared DNA, not actual generational kinship. Most of those shown on the map were 4th cousins or higher.
The vertical axis is logarithmic, so the actual increase in distance as the kinship increases is much greater than it appears. The trend line shown is exponential, which ironically looks straight because the Y-axis is already logarithmic. In my case, then, it seems clear that generally the more distant the kinship (i.e. “blood” relationship) the farther my relatives are from me. I suspect that is true generally, but I’d be interested in seeing demographic trends for the U.S. and world populations. I’d guess that in the less developed countries, families stay closer together for more generations. I found dozens of charts and articles online, but none that answer this question directly. Of course, such demographic trends change, and can do so rapidly. A number of recent articles mention how more millenials are living with their parents, reversing the trends of recent years. Whatever the trends, it’s fun to see how widespread my family is, even if I don’t know many of them.