2024 May
2nd month of the 2nd quarter of the 34th year of the Bush-Clinton-Shrub-Obummer/BiteMe-Trump-BiteMe/Harass economic mega-depression
updated: 2024-03-21
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"'Those who wish to enjoy peace must be ready for war.', [Epaminondas] lectured them [in 370BCE], 700 years before Vegetius's more famous Roman dictum, Qui desiderat pacem, praeparat bellum." --- Victor Davis Hanson 1999 _The Soul of Battle: From Ancient Times to the Present Day, How 3 Great Liberators Vanquished Tyranny_ pg54
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2024 May, week 1 (01-04) (16KB)
2024 May, week 2 (05-11) (16KB)
2024 May, week 3 (12-18) (16KB)
2024 May, week 4 (19-25) (16KB)
2024 May, week 5 (26-31) (16KB)
captain William Scott's flag for the Republic of Texas.
2024 May
2nd month of the 2nd quarter of the 34th year of the Bush-Clinton-Shrub-Obummer/BiteMe-Trump-BiteMe/Harass economic mega-depression
2024 May, week 1 (01-04) (16KB)
2024 May, week 2 (05-11) (16KB)
2024 May, week 3 (12-18) (16KB)
2024 May, week 4 (19-25) (16KB)
2024 May, week 5 (26-31) (16KB)
Proposed Bills 2024
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"total imports in 1930 added up to only 4% of the GNP and Smoot-Hawley applied to only a third of that, or 1.3% of the GNP. Is it conceivable that an increase in tariffs on 1.3% of the GNP triggered the collapse of 5K banks, wiped out five-sixths [about 83%] of the [total valuation of securities traded in the] stock market, caused adrop of 46% in the GNP, and sent unemployment soaring to 25%? One economist who studied the consequences of Smoot-Hawley writes that 'from 1929 to 1933, [USA's] GNP fell from $104G to $56G, a loss of $48G. However, net exports [from the USA] fell by only $700M, and domestic spending declined by $47.3G. IOW, net exports decreased by 1.5% of the fall in GNP, as domestic demand fell by the remaining 98.5%! It is patently absurd to fuss over that 1.5% fall and over-look the other 98.5%.'... With the crash, the stampede for cash to meet [vastly excessively leveraged] margin calls, the run on the banks, their collapse, and the wipe-out of savings, one-third of [USA's currency] supply vanished... crippling 1932 hike in the income tax, raising the top rate from 25% to 65%, and the bottom rate by a factor of 10, from 0.4% to 4%. To raise taxes in a recession is suicidal. FDR compounded the [offensive error] by raising the top rate to 79%!" --- Patrick Joseph Buchanan 1998 _The Great Betrayal: How American Sovereignty and "Social Justice" Are Being Sacrificed to the Gods of the Global Economy_ pp247-249 (citing Alfred E. Eckes ii 1995, 2000 _Opening America's Market: USA Foreign Policy since 1776_ chapter4 pp100-139; Batra 1996 _The Great USA Deception: What Politicians Won't Tell You About Our Economy and Your Future_ pg76; John Steele Gordon 1997, 2010 _Hamilton's Blessing: The ExtraOrdinary Life and Times of Our National Debt_ pp116-117; Thomas J. DiLorenzo 2008, 2009 _Hamilton's Curse: How Jefferson's Arch Enemy Betrayed the American Revolution and What It Means for USA Citizens Today_)
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ox, house, camel, door, window, peg/nail, sword, fence, snake, hand, palm-of-hand, ox-goad/lamp/lantern/lanthorn, water, fish, prop/support/post, eye, mouth, fishing-hook, back-of-head/monkey, head/top/beginning/first, tooth, t
alfa (α), beta (β), gamma (γ), delta (δ), epsilon (ε), zeta (ζ), eta (η), theta (θ), iota (ι), kappa (κ), lambda (λ), mu (μ), nu (ν), xi (ξ), omicron (ο), pi (π), rho (ρ), sigma (σ), tau (τ), upsilon (υ), phi/fi (φ), chi (χ), psi (ψ), omega (ω)
A, B, C, D, E, F, G, H, I, J, K, L, M, N, O, P, Q, R, S, T, U, V, W, X, Y, Z
alef (א), beth (ב), gimel (ג), daleth (ד), heh (ה), vav/w/u/o (ו), zayin (ז), chet (ח), teth (ט), yod (י), kaf (כ/ך), lamed (ל), mem (מ/ם), nun (נ/ן), samekh (ס), aayin (ע), pe/fay (פ/ף), tzaddi (צ/ץ), quoph (ק), resh/rash/rosh (ר), shin/sin (ש), tav/sav (ת)
| K | kilo- | thousand | | 10^3 | 1,000 |
| M | mega- | million | one thousand thousand | 10^6 | 1,000,000 |
| G | giga- | billion | one thousand million | 10^9 | 1,000,000,000 |
| T | tera- | trillion | one million million | 10^12 | 1,000,000,000,000 |
| P | peta- | quadrillion | one million billion | 10^15 | 1,000,000,000,000,000
|
| E | exa- | quintillion | one billion billion | 10^18 | 1,000,000,000,000,000,000
|
| Z | zetta- | sextillion | one billion trillion | 10^21 | 1,000,000,000,000,000,000,000
|
| Y | yotta- | septillion | one trillion trillion | 10^24 | 1,000,000,000,000,000,000,000,000
|
| R | ronna- | octillion | one thousand trillion trillion | 10^27 | 1,000,000,000,000,000,000,000,000,000
|
| Q | quecca- | nonillion | one million trillion trillion | 10^30 | 1,000,000,000,000,000,000,000,000,000,000
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Except that computer people use 2 as a base raised to multiples of powers of 10, instead of 10 raised to multiples of powers of 3 because powers of 2 are handier for them, but they also want to stay somewhat close to the values of 10 most folks are used to.
| 1 024 | K | kilo- (kibi-) | 2^10 |
| 065 536 | ? | ??? | 2^16 |
| 131 072 | ? | ??? | 2^17 |
| 262 144 | ? | ??? | 2^18 |
| 524 288 | ? | ??? | 2^19 |
| 001 048 576 | M | mega- (mebi-) | 2^20 |
| 001 073 741 824 | G | giga- (gibi-) | 2^30 |
| 002 147 483 648 | ? | ??? | 2^31 |
| 004 294 967 296 | ? | ??? | 2^32 |
| 001 099 511 627 776 | T | tera- (tebi-) | 2^40 |
| 001 125 899 906 842 624 | P | peta- (pebi-) | 2^50 |
| 001 152 921 504 606 846 976 | E | exa- (exbi-) | 2^60 |
| 002 305 843 009 213 693 952 | ? | ??? | 2^61 |
| 004 611 686 018 427 387 904 | ? | ??? | 2^62 |
| 009 223 372 036 854 775 808 | ? | ??? | 2^63 |
| 018 446 744 073 709 551 616 | ? | ??? | 2^64 |
| 036 893 488 147 419 103 232 | ? | ??? | 2^65 |
| 001 180 591 620 717 411 303 424 | Z | zetta- (zebi-) | 2^70 |
| 001 208 925 819 614 629 174 706 176 | Y | yotta- (yobi-) | 2^80 |
| 002 417 851 639 229 258 349 412 352 | ?? | ??? | 2^81 |
| 004 835 703 278 458 516 698 824 704 | ?? | ??? | 2^82 |
| 009 671 406 556 917 033 397 649 408 | ?? | ??? | 2^83 |
| 019 342 813 113 834 066 795 298 816 | ?? | ??? | 2^84 |
| 038 685 626 227 668 133 590 597 632 | ?? | ??? | 2^85 |
| 077 371 252 455 336 267 181 195 264 | ?? | ??? | 2^86 |
| 154 742 504 910 672 534 362 390 528 | ?? | ??? | 2^87 |
| 309 485 009 821 345 068 724 781 056 | ?? | ??? | 2^88 |
| 618 970 019 642 690 137 449 562 112 | ?? | ??? | 2^89 |
| 001 237 940 039 285 380 274 899 124 224 | ?? | ??? | 2^90 |
| 002 475 880 078 570 760 549 798 248 448 | ?? | ??? | 2^91 |
| 004 951 760 157 141 521 099 596 496 896 | ?? | ??? | 2^92 |
| 009 903 520 314 283 042 199 192 993 792 | ?? | ??? | 2^93 |
| 019 807 040 628 566 084 398 385 987 584 | ?? | ??? | 2^94 |
| 039 614 081 257 132 168 796 771 975 168 | ?? | ??? | 2^95 |
| 079 228 162 514 264 337 593 543 950 336 | ?? | ??? | 2^96 |
| 158 456 325 028 528 675 187 087 900 672 | ?? | ??? | 2^97 |
| 316 912 650 057 057 350 374 175 801 344 | ?? | ??? | 2^98 |
| 633 825 300 114 114 700 748 351 602 688 | ?? | ??? | 2^99 |
| 001 267 650 600 228 229 401 496 703 205 376 | ?? | ??? | 2^100 |
| 002 535 301 200 456 458 802 993 406 410 752 | ?? | ??? | 2^101 |
| 005 070 602 400 912 917 605 986 812 821 504 | ?? | ??? | 2^102 |
| 010 141 204 801 825 835 211 973 625 643 008 | ?? | ??? | 2^103 |
| 020 282 409 603 651 670 423 947 251 286 016 | ?? | ??? | 2^104 |
| 040 564 819 207 303 340 847 894 502 572 032 | ?? | ??? | 2^105 |
| 081 129 638 414 606 681 695 789 005 144 064 | ?? | ??? | 2^106 |
| 162 259 276 829 213 363 391 578 010 288 128 | ?? | ??? | 2^107 |
| 324 518 553 658 426 726 783 156 020 576 256 | ?? | ??? | 2^108 |
| 649 037 107 316 853 453 566 312 041 152 512 | ?? | ??? | 2^109 |
| 001 298 074 214 633 706 907 132 624 082 305 024 | ?? | ??? | 2^110 |
| 002 596 148 429 267 413 814 265 248 164 610 048 | ?? | ??? | 2^111 |
An alternate set of prefixes has been proposed.
3. 14159 26535 89793 23846 26433 83279 50288 41971 69399 37510 58209 74944 59230 78164 06286 20899 86280 ≅ π
Congressional candidate fund-raising, expenditures, and debt
World + USA Over-Population Clocks
Jimbo Wales's WikiPedia on World Over-Population
population density
countries by population density
USA states and counties by population density
World Atlas: states by population density
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"Yet Americans kept slipping [being shoved] down the job ladder. At first it was jobs in the lower-paid sectors of manufacturing that went over-seas. Then it was skilled work in automobiles, steel, machinery, and electronics. By 2008, 48% of all sales by Standard & Poor's top 500 USA corporations were of items produced outside the USA. Not to worry, the laid-off workers and their children were told: they would be re-trained and educated for high-paying service-sector jobs in the new world of computerized technology Such jobs would always be generated in the USA because of our advanced technology, prestigious universities, and Nobel Prize-winning scientists. The share of the work-force with college degrees doubled, and millions of students took out loans to learn computer science. But the rest of the world, now having access to American consumers [and USA universities] also went to school. India and [Red China] turned out scientists and engineers at a phenomenal rate [including a lot of 2-year shade-tree mechanics they lumped in with counts of engineers]. Projections by the BLS in 2006 concluded that by 2014 the number of occupations filled by people with college degrees will rise by merely 1%-point, from 28% to 29%. The share of jobs for which a college education will actually be required is projected to be just 21%. It turned out that much of the job and wealth creation associated with the information economy was tied to the making of goods; success results from setting trained people to work on problems in the context of day-to-day production [i.e. having design engineers in or near the factories and complaints departments], whether of sneakers, automobiles, pharmaceuticals, or Hollywood films. The more [the business executives] off-shored production jobs, the more [they] off-shored research and development as well. What had been touted as a natural comparative advantage [not to be confused, as Jeff Faux does, with absolute advantage] for the USA in skills, technology, and organization was in reality duplicated or even surpassed by other nations. 'American' trans-national corporations [their executives and boards] were locating their research and development departments in India, Taiwan, and [Red China], where the skills were [being increased] and came cheap. Soon IBM had more employees in [Red China] than in the USA. Apple had 25K workers in the USA and about 250K on contract in [Red China]. An analysis of 57 major research initiatives of the US telecommunications industry showed that all but 5 were located outside the USA. According to one estimate, 80% of engineering tasks in product development can be 'easily out-sourced'. Jack Welsh, the celebrated CEO of General Electric, proclaimed a '70-70-70' rule: At least 70% of research and development would be out-sourced. At least 70% of that would be off-shored. At least 70% of that would be off-shored to India. By the middle of the first decade of the 21st century, the majority of GE's employees were over-seas. During that decade, USA high-tech employment remained at 3.8M jobs, and wages and salaries were stagnant [while inflation eroded earnings &hundreds of thousands of USA citizens graduated with STEM major degrees each year]. Meanwhile, multi-national [company executives and boards and their lobbyists] pressured the USA government to allow them to bring in foreign workers to be trained by Americans whose jobs they would take back home. One result is to further obscure the effect of off-shoring on high-wage jobs in the public debate. For example, professor Ron Hira of the Rochester Institute of Technology [and later Howard U] points to the example of Cognizant Technology Solutions Corporation, a Fortune 500 [co-based in the USA and India, cross-border bodyshop and off-shoring firm] that has been on Fortune magazine's list of the 10 fastest-growing US firms for the last 9 years. Between 2009 and 2010 Cognizant's sales to the financial and health care sector in the USA gew by about $1G. Of the new jobs created [by Cognizant] 15,450 went to India. The company reported that the rest were hired in the USA, but as Hira points out, almost all of the USA hires went to foreigners on temporary work visas. So the net contribution to opportunities for USA worker was just about zero. Hira estimates that some 1.3M high-tech jobs were created in India for serviing the USA market." --- Jeff Faux 2012 _The Servant Economy_ pp77-78 (citing Heidi Shierholz, Jared Bernstein & Lawrence Mishel 2008 _The State of Working America 2008/2009_; 2005-03-21 "OutSourcing Innovation" _BusinessWeek_; Ron HIra 2010-10-14 "The H01B/L-1 Visa Programs: Out of Control" http://www.epi.org/publication/bp280 ; Ron Hira 2012-01-08 e-mail message to Jeff Faux)
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