Trego's Mountain Ear

"Serving North Lincoln County"

Tag: Demography

  • Statistically Remote Doesn’t Mean Impossible

    My post-Uvalde thoughts move toward hardening our own little school.  School shootings are always statistically unlikely.  The timeline at Uvalde shows that at 11:27, a teacher props the door open. It remains open for 6 minutes before the crazy little bastard enters the school.  He doesn’t close it – the door remains open and is the access point for police.  A safety protocol broke down.  The crazy little bastard had a six-minute window of opportunity.  Twenty-one people died and 17 more were wounded.  Six minutes.

    In demography, our phrase is “Malthus only has to be right once.”  I listened to a Fed describing terrorist attacks  – “They have to get lucky once.  We have to get it right every day.”  The exercise showed how hard that was.  A teacher, secure in the misbelief that a statistically unlikely event wouldn’t happen, propped a door open.  For 6 minutes.  The crazy got in.  The statistically unlikely event happened.  We play poker hoping for statistically unlikely events to occur. 

    It’s easy to look at the police failures – but the initial failure was the teacher who wedged the door open . . . secure in the belief that there was no risk in violating that simple safety protocol.  Staying alert, maintaining security against something that does not occur, day after day, is difficult. 

    I can think of many situations where a teacher wouldn’t want to keep unlocking the door.  It’s Spring – the time when contracts are, or are not renewed.  We’ve had that this year at Trego – and seen a bit of hostility over it.  It gives me a perspective that, in Uvalde, the shooter gained access not through police failure, but through a teacher’s carelessness.  I can understand both carelessness and resentment.

    I have forgotten the name of the teacher who left his female engineering students to be killed at the Montreal Polytechnique Massacre.  I hope he came to some sort of grips with his failure – I know I could not have accepted that decision had it been mine.  Perhaps the Uvalde teacher who spent 20 lives for easier access to the door can come to grips with that conduct.  I would hate to have to rationalize it had it been my blunder.

    It is difficult to stay constantly on the alert for the statistically unlikely occurrence.  Years of boredom are eventually interrupted by a few minutes of stark terror.  Uvalde’s police, like Parkland’s, made poor choices – but the timeline shows that a teacher who propped the door open had the best opportunity to eliminate the shooter’s opportunity.  Was it just casual carelessness?  Was it carelessness coupled with resentment?  I do not know – but I have read the pricetag, and it was too high.

  • It Isn’t One Citizen One Vote

    When it comes to the House of Representatives, I’m a Constitutional scholar.  Specifically Article 1, Section 2 – “The House of Representatives shall be composed of Members chosen every second Year by the People of the several States, and the Electors in each State shall have the Qualifications requisite for Electors of the most numerous Branch of the State Legislature.

    No Person shall be a Representative who shall not have attained to the Age of twenty five Years, and been seven Years a Citizen of the United States, and who shall not, when elected, be an Inhabitant of that State in which he shall be chosen.

    (Representatives and direct Taxes shall be apportioned among the several States which may be included within this Union, according to their respective Numbers, which shall be determined by adding to the whole Number of free Persons, including those bound to Service for a Term of Years, and excluding Indians not taxed, three fifths of all other Persons.) (The previous sentence in parentheses was modified by the 14th Amendment, section 2.) The actual Enumeration shall be made within three Years after the first Meeting of the Congress of the United States, and within every subsequent Term of ten Years, in such Manner as they shall by Law direct. The Number of Representatives shall not exceed one for every thirty Thousand, but each State shall have at Least one Representative; and until such enumeration shall be made, the State of New Hampshire shall be entitled to chuse three, Massachusetts eight, Rhode Island and Providence Plantations one, Connecticut five, New York six, New Jersey four, Pennsylvania eight, Delaware one, Maryland six, Virginia ten, North Carolina five, South Carolina five and Georgia three.

    When vacancies happen in the Representation from any State, the Executive Authority thereof shall issue Writs of Election to fill such Vacancies.

    The House of Representatives shall chuse their Speaker and other Officers; and shall have the sole Power of Impeachment.”

    The lines highlighted in yellow govern the decennial Census and apportionment of Congresscritters.  Congresscritters are apportioned according to population – not according to the number of citizens a state has.  As you look at the data, you can see that one out of each seven people represented by a California Congresscritter isn’t a US Citizen. 

    If Congress were to pass a law requiring seats in the House of Representatives be apportioned based on citizens instead of population, California would probably lose 5 seats, New York and Florida each 2, and New Jersey  and Illinois 1 each.  Somehow, I don’t think it will happen.

    State demographics by citizenship status|
    Citizenship status of residents, 2014

     State Total Population NativeForeign-born
    Total    		Foreign-born
    Naturalized    		Foreign-born
    Non-citizen
    Alabama4,817,6784,651,201166,47755,514110,963
     100.0%96.5%3.5%1.2%2.3%
    Alaska728,300676,62051,68027,91023,770
     100.0%92.9%7.1%3.8%3.3%
    Arizona6,561,5165,677,869883,647339,481544,166
     100.0%86.5%13.5%5.2%8.3%
    Arkansas2,947,0362,811,266135,77040,38495,386
     100.0%95.4%4.6%1.4%3.2%
    California38,066,92027,776,28410,290,6364,911,8995,378,737
     100.0%73.0%27.0%12.9%14.1%
    Colorado5,197,5804,690,377507,203192,391314,812
     100.0%90.2%9.8%3.7%6.1%
    Connecticut3,592,0533,101,593490,460235,507254,953
     100.0%86.3%13.7%6.6%7.1%
    Delaware917,060840,18176,87935,52741,352
     100.0%91.6%8.4%3.9%4.5%
    District of Columbia633,736545,11088,62634,48354,143
     100.0%86.0%14.0%5.4%8.5%
    Florida19,361,79215,571,9633,789,8291,960,0091,829,820
     100.0%80.4%19.6%10.1%9.5%
    Georgia9,907,7568,945,010962,746371,908590,838
     100.0%90.3%9.7%3.8%6.0%
    Hawaii1,392,7041,143,424249,280140,906108,374
     100.0%82.1%17.9%10.1%7.8%
    Idaho1,599,4641,503,82995,63534,22961,406
     100.0%94.0%6.0%2.1%3.8%
    Illinois12,868,74711,081,8211,786,926838,686948,240
     100.0%86.1%13.9%6.5%7.4%
    Indiana6,542,4116,229,726312,685112,699199,986
     100.0%95.2%4.8%1.7%3.1%
    Iowa3,078,1162,934,406143,71054,01789,693
     100.0%95.3%4.7%1.8%2.9%
    Kansas2,882,9462,687,052195,89468,325127,569
     100.0%93.2%6.8%2.4%4.4%
    Kentucky4,383,2724,235,463147,80952,65395,156
     100.0%96.6%3.4%1.2%2.2%
    Louisiana4,601,0494,419,407181,64272,250109,392
     100.0%96.1%3.9%1.6%2.4%
    Maine1,328,5351,281,40647,12925,63121,498
     100.0%96.5%3.5%1.9%1.6%
    Maryland5,887,7765,050,375837,401397,433439,968
     100.0%85.8%14.2%6.8%7.5%
    Massachusetts6,657,2915,639,9251,017,366520,931496,435
     100.0%84.7%15.3%7.8%7.5%
    Michigan9,889,0249,278,502610,522308,236302,286
     100.0%93.8%6.2%3.1%3.1%
    Minnesota5,383,6614,980,116403,545193,791209,754
     100.0%92.5%7.5%3.6%3.9%
    Mississippi2,984,3452,917,37466,97123,49843,473
     100.0%97.8%2.2%0.8%1.5%
    Missouri6,028,0765,792,081235,995103,033132,962
     100.0%96.1%3.9%1.7%2.2%
    Montana1,006,370985,85020,52010,8949,626
     100.0%98.0%2.0%1.1%1.0%
    Nebraska1,855,6171,735,200120,41742,72177,696
     100.0%93.5%6.5%2.3%4.2%
    Nevada2,761,5842,234,549527,035233,551293,484
     100.0%80.9%19.1%8.5%10.6%
    New Hampshire1,321,0691,247,65773,41238,52934,883
     100.0%94.4%5.6%2.9%2.6%
    New Jersey8,874,3746,969,9691,904,405989,166915,239
     100.0%78.5%21.5%11.1%10.3%
    New Mexico2,080,0851,874,204205,88170,926134,955
     100.0%90.1%9.9%3.4%6.5%
    New York19,594,33015,218,3854,375,9452,317,7872,058,158
     100.0%77.7%22.3%11.8%10.5%
    North Carolina9,750,4059,009,170741,235240,268500,967
     100.0%92.4%7.6%2.5%5.1%
    North Dakota704,925684,37020,5557,48413,071
     100.0%97.1%2.9%1.1%1.9%
    Ohio11,560,38011,091,189469,191233,953235,238
     100.0%95.9%4.1%2.0%2.0%
    Oklahoma3,818,8513,604,070214,78170,846143,935
     100.0%94.4%5.6%1.9%3.8%
    Oregon3,900,3433,516,357383,986150,498233,488
     100.0%90.2%9.8%3.9%6.0%
    Pennsylvania12,758,72911,976,626782,103401,469380,634
     100.0%93.9%6.1%3.1%3.0%
    Rhode Island1,053,252915,234138,01870,04967,969
     100.0%86.9%13.1%6.7%6.5%
    South Carolina4,727,2734,500,820226,45381,502144,951
     100.0%95.2%4.8%1.7%3.1%
    South Dakota834,708810,30824,4009,09615,304
     100.0%97.1%2.9%1.1%1.8%
    Tennessee6,451,3656,146,570304,795109,057195,738
     100.0%95.3%4.7%1.7%3.0%
    Texas26,092,03321,795,0854,296,9481,454,6722,842,276
     100.0%83.5%16.5%5.6%10.9%
    Utah2,858,1112,618,427239,68484,697154,987
     100.0%91.6%8.4%3.0%5.4%
    Vermont626,358600,17826,18015,20110,979
     100.0%95.8%4.2%2.4%1.8%
    Virginia8,185,1317,236,647948,484454,434494,050
     100.0%88.4%11.6%5.6%6.0%
    Washington6,899,1235,978,429920,694427,201493,493
     100.0%86.7%13.3%6.2%7.2%
    West Virginia1,853,8811,826,34127,54012,96914,571
     100.0%98.5%1.5%0.7%0.8%
    Wisconsin5,724,6925,456,268268,424114,684153,740
     100.0%95.3%4.7%2.0%2.7%
    Wyoming575,251555,91519,3367,06312,273
     100.0%96.6%3.4%1.2%2.1%
    Source: United States Census Bureau, “Selected Characteristics of the Native and Foreign-Born Populations”
  • Wells-Barnett Becoming Barbie

    Wells-Barnett Becoming Barbie

    I note that Mattel is making a Barbie doll that honors Ida Wells-Barnett.

    They note that she was a journalist, suffragette, and had a role in founding the NAACP – to me, her unusual strength was the use of statistics in her research on lynchings.  She deserves mention in her early role in social research and reliance on statistics.  Still, the article doesn’t include the quote that I find easy to remember:

    I’m a Montanan.  My state’s legal tradition begins with vigilantes hanging a crooked sheriff and his minions.  In 1884, Granville Stuart organized another vigilance committee – now known as Stuart’s Stranglers – to end rustling.  In a short time, Stuart’s Stranglers killed at least 20 rustlers, and numbers up to 100 are written in some accounts.  By the end of the Summer, Granville Stuart was president of the Stockman’s Association.  Stuart’s activities, despite the poor record keeping, made 1884 the highest year for lynching white men in the US. (My readings suggest that the first recorded use of the numbers 3-7-77 was by Stuart’s Stranglers and not by the Vigilantes of Montana 20 years earlier)

    Douglas Linder has published the data series Ida Wells started (maintained at Tuskegee) on lynchings by state and race. Clicking the link will give you an idea of how solid the lady’s research was – and how racist it was in some areas.

    I’ll be looking for the Barbie – but I want mine to be holding a lever action Winchester.  She may not have been granted a graduate degree – but her work was important in developing American Sociology.

  • Our Communities by ACS Numbers

    I listened to a comment about the median household income in Trego – and defaulted to my professional statement before retirement – “That’s American Community Survey data, and it’s not very good for small communities.”  When I checked it, the $36,458 median household income for Trego translates as “somewhere between $27,478 and $45,438.  ACS data has its uses, but it has to be used with a lot of caution.

    So here’s a little ACS data on our communities – you can check for margin of error (MOE) here.   I wouldn’t recommend using any of the numbers without reviewing MOE – but just sharing the data shows the variance.  It’s safe to admit that my household was one selected for the ACS. With two retirees at home, I didn’t hurt Trego’s school enrollment rate, I raised the percentage of bachelors degree or above, kept the employment rate down, and raised the median age.

    Trego CDPFortine CDPEureka CCDRexford Town
    Population5153176,47078
    Median Age60.527.950.153.3
    Median Household Income$36,458$68,036$40,827$30,481
    Bachelor’s Degree or more26.10%19.20%22.40%0.00%
    Veterans6.80%16.20%12.90%16.80%
    Poverty9.50%5.20%20.40%23.60%
    School Enrollment97.80%72.30%81.90%100%
    Employment Rate40.20%59.50%38.30%20.60%
    Housing Units2831773,71673
    Occupied Housing Units2371442,79646
    Disabilities31.10%18.80%26.70%65.90%
    Children under 189.30%32.50%22.10%13%

    It looks like the Fortine sample drew some younger respondents.  Eureka CCD with a larger population and larger sample is probably closer to correct, and the town of Rexford data is probably close to useless because the small sample size almost guarantees sampling bias

  • Tester for VP

    Tester for VP

    Politics is a numbers game.  The quality of data has gone down as folks have learned to avoid or even lie to pollsters.  This time, I am looking at a different set of numbers – basically a thought experiment.  Since my skills set is demography, not political science, the assumptions may be in error and the conclusion not connected with the real world.  That said, here’s the idea. 

    It seems inevitable that Biden is on his way out as  president.  Whether he just owns up to his declining mental facilities and resigns, is removed on 25th amendment grounds,  just physically collapses, or is impeached he is well past his “best used by” date.  That means President Kamala Harris and no vice-president.  Anything takes Kamala out and we have President Pelosi. 

    Normally there would be a raft full of contenders – but these are not normal times.  The Dem majority in the Senate depends on VP Harris being able to cast a tie breaking vote.  President Harris will not have that ability.  She will have to nominate a vice-president who can be approved by a majority vote in the House of Representatives and in the Senate. 

    Nancy Pelosi can whip the House Dems in line to approve just about anything as our new VP.  Right now, the house has 212 repugnants, 220 dims, and 3 vacancies.  The House of Representatives will pretty much approve anyone appointed by Harris – but the Senate is a different story.  Balanced 50-50, with President Harris you won’t have a majority leader and a minority leader any more.  Mitch McConnell’s power increases tremendously in this situation.  That changes the universe of potential vice-presidents.  Someone close to McConnell should share this with him – he’s not on my speed dial, and I am surely not on his.

    McConnell could probably arrange 100% support for our next VP if he’s a democrat senator from a state with a republican governor.  Only 7 states have republican governors and democrat senators.  Massachusetts ain’t gonna happen.  Montana can.

    That coarse calculation makes Tester’s chance one in six.  Financially, it would be a good deal – a senator’s salary is $174,000 and becoming VP would raise that to $235,100.  What Big Sandy farmer wouldn’t accept a promotion that brought a $60,000 raise?  A 35% raise for the last 3 years before retirement would jack the pension.  My bet is he’d take the gig if it were offered.

    I’m not sure what advantages that Vice-President Tester would bring to Montana – but he would have to be better for us than the last four or five VPs have been.  I do believe that a Montana farmer could do more for the nation as Vice-President.  We’re in a spot where it just might happen.  In 2016 the choice was Hillary or Trump.  In 2020 the choice was Trump or Biden.  At least I kind of like Tester – and Bob Brown assures me that he shoots gophers, and is a good shot from prone.  Let’s get ready to lobby – it might just happen. 

  • Measuring Migration

    When you work with Census data, migration numbers can be very precise – but the 10 years between each Census often make the data obsolete.  As demographers, we had to find ways to work around that – and U-Haul had the websites that let me better understand and explain migration.

    For example, if I price renting a 15’ truck in Bakersfield, California, heading to Eureka, Montana, I get a price quote of $5,173 today.  On the other hand, it costs $1,109 to rent the same truck in Eureka and drive it to Bakersfield.

    If I want to see beautiful Bend, Oregon in the rear view mirror of my 15’ rental truck, the website tells me the trip to Eureka, MT is $3,052.  Renting the same truck in Eureka, to go to Bend is only $654.

    I didn’t learn to abuse U-Haul’s website in a classroom – I got the general idea while riding a bus seated alongside a very successful retarded guy.  He made a living riding the bus – back then there was a pass that was good for six months travel in country – and then driving a car or small truck back to Denver.  He may not have completed high school – but he gave me the foundation of a method to quantify migration.  Obviously, Bakersfield and Bend have more people trying to leave, and Eureka has more inmigration. 

    If we look at the trip from Minneapolis to Eureka, it’s $1,703.  Eureka to Minneapolis is $1,362.  Park City, Utah showed up as $990 to Eureka, while Eureka to Park City was $495. 

    It provides a better feel for migration in central locations like Park City – where you can go in any direction.  You can’t go north from Eureka in this time of Covid – and you can’t drive west from California.  Still, it gives data in something resembling a ratio – the challenge the rental truck industry has is getting the trucks from destination locations (inmigration) back to the places they came from (outmigration) without hiring my friend with the Greyhound pass.

    TaxFoundation.org gives last year’s data, and it is massaged and compiled from more moving companies.  Guess what?  The top destination state (inmigration) is Idaho – and Idaho has a lot of similarities to western Montana.  Oregon was a destination state – and still needs the rental trucks from Eureka to keep things going.  I think the last person renting a truck to leave New Jersey might want to turn the lights off as he or she pays the last toll to drive out.

    I’ve rented U-Haul trucks a couple of times – but the company has provided me a lot of comparative data on migration during my career.  It’s still science, and it’s still numbers driven.