How Did We Get To Where We Are Today With People Living On The Streets?

How Did We Get To Where We Are Today With People Living On The Streets? 

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Corporate America executives have not taken reductions in pay and benefits since 1980. Instead, their total compensation has skyrocketed. While union and typical worker wages stagnated, executive pay experienced historic exponential growth.

According to data from the EconomicPolicy Institute (EPI), inflation adjusted CEO compensation at the largest U.S. companies grew by 1,094%between 1974 and 2024.

The Exploding Pay Gap

Executive compensation shifted from being primarily salary based to heavily reliant on equity and market incentives.

  • Widening Ratios: In 1965, the CEO to typical worker ratio was 21 to 1. By 1989 it was 58 to 1, and peaked to 408 to 1 in 2021.
  • Realized vs. Granted Pay: Executives leveraged the stock market boom. By cashing out stock options and vested shares at opportune times, their realized take home pay vastly outperformed their initial base contracts.
  • Spillover Effect: This dramatic rise was not limited to CEOs. Outsized compensation structures trickled down, pulling up the salaries of chief financal officers, vice presidents, and senior management across corporate America.

Shifts in Benefits and “Golden Parachutes”

Unlike Standard labor contracts where benefits were cut, executive benefits were heavily enhanced and protected 

  • Insulated Pensions: While Companies phased out traditional defined-benefit pensions for average workers, executives were granted generous Supplemental Executive Retirement Plans (SERPS) that guaranteed multi-million dollar payouts regardless of market shifts.
  • Golden Parachutes: Multi-million dollar exit packages became standard practice. Executives frequently received massive payouts even when leaving a company due to poor performance or corporate restructuring.
  • Perks and Tax Advantages: Executive packages routinely incorporated unique perks such as personal use of corporate jets, comprehensive estate planning services, and tax advantaged deferred compensation structures

Why Executive Pay Soared After 1980

  • The Deregulation Era: The economic policies of the 1980s prioritized maximizing shareholder value above all else, tying executive performance to stock prices.
  • Plummeting Tax Rates: The top marginal income tax rates dropped dramatically under the Reagan administration, creating an incentive for corporate boards to award drastically higher cash and stock bonuses.
  • Compound Benchmarking: Corporate compensation committees began hiring specialized consulting firms to benchmark pay. To appear competitive, almost every company aimed to pay their executives in the top quartile, causing an artificial upward spiral in compensation scales. 

Union workers have experienced significant, widespread cuts in pay, benefits, and retirement security since 1980, primarily driven by a structural shift known as “concessionary bargaining.” 

1. The 1980s: The Era of Wage Concessions 

The early 1980s marked a sharp turning point for labor power, triggered by the 1981–1982 recession, deregulation of major industries, and President Ronald Reagan breaking the PATCO air traffic controllers strike in 1981. This catalyzed a wave of historic rollbacks:

  • Companies began widely adopting two-tier systems—such as wage and benefit structures—during the economic recessions and high inflation of the early 1980s. They became common across industrialized economies as a way to lower labor costs for new hires while protecting the pay of senior workers.

Two-Tier Wage Systems: To protect senior workers, unions were forced to accept “two-tier” structures. Introduced prominently by companies like American Airlines in 1983, these agreements mandated that newly hired union workers would permanently make significantly lower wages and receive fewer benefits than senior staff for doing the exact same job   

  • Lump-Sum Substitutes: Rather than receiving permanent hourly wage increases that compounded over time, unions increasingly accepted one-time lump-sum bonuses during contract renewals, effectively stagnating baseline career pay.  

2. The 1990s to 2010s: The Destruction of Benefits

As direct wage cuts stabilized, the landscape shifted toward dismantling the robust benefit packages unions had won in the mid-20th century.

  • The Loss of Pensions: Traditional defined-benefit pensions were systematically eliminated for new hires. Airlines (United, US Airways) defaulted on their pensions entirely, while auto and manufacturing giants implemented “hard freezes.” This forced union workers out of guaranteed lifelong retirement payouts and into riskier, employee-funded 401(k) plans. 
  • Healthcare Cost-Shifting: Escalating medical costs led employers to demand massive concessions on health insurance. Unions went from enjoying fully employer-paid, zero-deductible healthcare plans to absorbing steadily rising premiums, higher deductibles, and reduced coverage.
  • Bankruptcy as a Weapon: Under Chapter 11 bankruptcy provisions, federal judges repeatedly allowed struggling corporations—such as Continental Airlines in 1983 and major steel mills in the 2000s—to legally void active union contracts, instantly wiping out negotiated pay scales and retiree medical benefits overnight.

Traditional private-sector pensions did not disappear overnight; instead, they gradually phased out between the mid-1980s and the early 2000s, replaced by employee-funded 401(k) plans. The number of single-employer pension plans in the United States peaked around 1985 and has declined steadily ever since. 

According to data from the Federal Reserve Bank of St. Louis, the share of private-sector workers covered by traditional “defined-benefit” pensions plummeted from 59% in 1989 to just 21% by 2022, while 401(k)-style “defined-contribution” plans surged from 55% to 83% over the same timeframe. 

  • 1978–1981 (The Catalyst): Congress passed the Revenue Act of 1978, which included Section 401(k). By 1981, the IRS cleared the way for companies to use this tax code to allow employees to defer pre-tax salary into retirement accounts 
  • Mid-1980s (The Peak): The total number of private pension plans peaked around 1985. New financial accounting rules forced corporations to list future pension liabilities directly on their balance sheets, making them look less profitable to investors. 
  • The 1990s & 2000s (The Great Freeze): Major corporations realized they could cut massive structural expenses by shifting the financial risk of market downturns entirely to the employee. Throughout the 2000s, household names like IBM, Verizon, and General Electric enacted “hard freezes” on their pension plans, stopping new accruals and transitioning workers to 401(k)s 

1. Major Pension Terminations (The 2000s Crisis) 

  • United Airlines (2005): Executed the largest corporate pension default in U.S. history. United dumped all four of its employee plans onto the PBGC, shorting its workforce by $9.8 billion. High-earning workers like pilots faced pension cuts of up to 50% to 70% due to federal statutory payment caps. 
  • US Airways (2003–2005): Over two separate bankruptcies, the airline terminated all its employee pension plans. This passed $2.3 billion in unfunded liabilities directly to the PBGC. 
  • Delta Air Lines (2006): While navigating Chapter 11 bankruptcy, Delta terminated its pilots’ pension plan, which faced billions in shortfalls. However, Delta successfully saved and froze the pension plans of its ground crew and flight attendants. 
  • American Airlines (2012): Upon entering bankruptcy, American initially sought to completely dissolve its plans. After intense pushback from labor unions and the PBGC over its $8.3 billion shortfall, American reached a deal to freeze the plans rather than terminate them. Active workers stopped building new pension credits but retained what they had earned, transitioning to 401(k) matches going forward. 

2. Historical Pension Takeovers (Pre-2000s) 

  • Trans World Airlines (TWA): Suffered chronic underfunding problems under corporate raider Carl Icahn. The PBGC eventually absorbed a $700 million shortfall across TWA’s worker and pilot retirement funds in 2001. 
  • Pan American World Airways (Pan Am): When the iconic carrier collapsed into bankruptcy in 1991, it left behind $621 million in underfunded pension liabilities. 
  • Eastern Air Lines: Collapsed in 1991, leaving roughly $700 million in underfunded commitments that required a federal pension rescue. 

3. The Structural Impact on Airline Labor 

AirlineDeficit Size at CrisisAction TakenWorker Outcome
United~$9.8 BillionTerminated (PBGC Takeover)Severe cuts up to 70% for some retirees.
US Airways~$2.3 BillionTerminated (PBGC Takeover)Massive cuts; plans held just 40% of required assets.
DeltaMulti-BillionPartially TerminatedPilots shifted to 401(k)s; other staff plans frozen.
American~$8.3 BillionHard FreezeAccruals stopped; past benefits safely preserved.

Beyond the major airlines, the largest corporate pension defaults and chronic underfunding crises in U.S. history occurred heavily within the automotive, steel, and manufacturing sectors. When the dot-com bubble burst and interest rates fell in the early 2000s, dozens of industrial giants saw their massive retirement pools crater into deep deficits.

1. The Automotive Giants 

The Detroit automakers operated some of the largest private pension funds in the world, which became crushing financial burdens when car sales plummeted:  

  • General Motors (GM): Historically held the largest corporate pension shortfall in American history, with its U.S. pension deficit topping $19.3 billion in 2002 and hitting roughly $20 billion ahead of its 2009 bankruptcy. GM avoided a federal takeover by injecting billions in cash and spinning off chunks of its liabilities. 
  • Chrysler: Faced multibillion-dollar pension shortfalls during its 2009 financial collapse, placing its extensive retirement obligations directly on the brink of a federal bailout before restructuring. 
  • Delphi Corporation: This massive auto parts manufacturer (spun off from GM) filed for bankruptcy in 2005. It executed one of the largest defaults ever, dumping $6.2 billion in underfunded pension liabilities onto the Pension Benefit Guaranty Corporation (PBGC). 

2. The Steel Industry Collapse 

In the early 2000s, structural shifts, foreign competition, and massive “legacy costs” for retired workers completely wiped out the traditional American steel industry: 

  • Bethlehem Steel (2002): Suffered a catastrophic collapse, defaulting on $3.7 billion in underfunded liabilities. Before the United Airlines crisis, this stood as the largest pension failure in U.S. history. 
  • LTV Steel (2002): Terminated its employee pension plans during a bitter bankruptcy, offloading $1.9 billion in underfunded debt to the federal government. 
  • National Steel (2002): Liquidated its assets and dumped a $912 million retirement shortfall onto the PBGC. 
  • Kaiser Aluminum (2004): Terminated multiple retirement structures, resulting in a $555 million pension shortfall. 

3. Notable Retail, Finance, and Tech Failures 

Economic recessions led several massive household brands to completely default on their promises to workers: 

  • Lehman Brothers (2008): Following its historic crash that triggered the global financial crisis, the investment bank left behind heavily underfunded pension funds taken over by the PBGC. 
  • Circuit City (2009): The electronics retail giant liquidated all stores, leaving its employee pension program entirely short on cash and forcing a federal rescue 
  • Sears (2018): After years of retail decline, Sears entered bankruptcy with a $1.4 billion pension deficit, forcing the PBGC to assume responsibility for the retirement benefits of 90,000 workers. 
  • Studebaker (1963): The historic automobile company’s sudden collapse left thousands of workers with zero retirement security. This single crisis was so influential it directly triggered Congress to pass the Employee Retirement Income Security Act (ERISA) of 1974, creating the PBGC backstop we use today. 

Summary of Historic Corporate Pension Crises

CompanySectorPeak Deficit / ShortfallFederal Takeover?
General MotorsAutomotive~$20 BillionNo (Restructured)
Delphi Corp.Auto Parts$6.2 BillionYes (PBGC Absorbed)
Bethlehem SteelIndustrial$3.7 BillionYes (PBGC Absorbed)
LTV SteelIndustrial$1.9 BillionYes (PBGC Absorbed)
SearsRetail$1.4 BillionYes (PBGC Absorbed)
National SteelIndustrial$912 MillionYes (PBGC Absorbed)

Signed by President Ronald Reagan, the Omnibus Reconciliation Act of 1981 slashed federal mental health spending by roughly 30%. It repealed the Mental Health Systems Act of 1980, ended direct categorical funding for community mental health centers, and replaced them with state-administered block grants.

  • Repeal of the 1980 Act: Erased Jimmy Carter’s Mental Health Systems Act, which had aimed to improve community care and protect patients’ rights. .
  • Block Grants: Shifted power and funding to state governments via the Alcohol, Drug Abuse, and Mental Health Services Block Grant. 
  • Funding Cuts: Reduced federal financial support for outpatient and community programs by nearly a third 

1955 was the peak mental health population at 560,000 inpatients at state and county mental health hospitals. Adjusted for today’s population that would equal over 1.1 million people. Today there are about 750,000 people experiencing homelessness. Draw your own conclusions. Today the number of psychiatric beds is roughly 3% of its 1955 peak. We need to reimagine and rebuild the institution of mental health care in America.

Keep in mind, the Crack Epidemic began in the 1980s.

Ron Jeremy Crossed with Danny Devito

I noticed the cleaning guy at work looks like Ron Jeremy in the face. I mentioned it to him. He said, most people thought he looked like Danny Devito.

Alex the cleaning guy

I said, oh yeah! You have Ron Jeremy’s head on Danny Devito’s body. Then I asked AI what it would look like if you put Ron Jeremy’s head on Danny Devito’s body. It answered, It would look like the guy that played the Penguin on Batman.

Then I asked AI to create a picture of Ron Jeremy’s head on Danny Devito’s body.

Ron Jeremy’s Head on Danny Devito’s Body.

Ordinary Least Squares vs. Geographically Weighted Regression Model for Philadelphia Building Code Violations Using R

OLS

> fit.ols<-glm(usarea ~ lmhhinc   + lpop + pnhblk + punemp + pvac  + ph70 + lmhval +

+                 phnew + phisp, data = philly2)

> summary(fit.ols)

Call:

glm(formula = usarea ~ lmhhinc + lpop + pnhblk + punemp + pvac + 

    ph70 + lmhval + phnew + phisp, data = philly2)

Coefficients:

            Estimate Std. Error t value Pr(>|t|)    

(Intercept)  534.491    164.270   3.254  0.00124 ** 

lmhhinc        2.462     12.176   0.202  0.83990    

lpop          -1.344      6.338  -0.212  0.83216    

pnhblk        21.158     18.077   1.170  0.24260    

punemp        -5.097     63.645  -0.080  0.93622    

pvac         371.699     58.427   6.362 5.96e-10 ***

ph70         -79.691     35.535  -2.243  0.02552 *  

lmhval       -45.668     10.458  -4.367 1.64e-05 ***

phnew         17.958    319.042   0.056  0.95514    

phisp        -56.308     30.695  -1.834  0.06741 .  

Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

(Dispersion parameter for gaussian family taken to be 4829.927)

    Null deviance: 2938287  on 375  degrees of freedom

Residual deviance: 1767753  on 366  degrees of freedom

AIC: 4268.4

Number of Fisher Scoring iterations: 2

GWR

gwr.fit1<-gwr(usarea ~ lmhhinc   + lpop + pnhblk + punemp + pvac  + ph70 + lmhval +phnew + phisp, data = philly2.sp, bandwidth = gwr.b1, se.fit=T, hatmatrix=T)

> gwr.fit1

Call:

gwr(formula = usarea ~ lmhhinc + lpop + pnhblk + punemp + pvac + 

    ph70 + lmhval + phnew + phisp, data = philly2.sp, bandwidth = gwr.b1, 

    hatmatrix = T, se.fit = T)

Kernel function: gwr.Gauss 

Fixed bandwidth: 1322.708 

Summary of GWR coefficient estimates at data points:

                   Min.    1st Qu.     Median    3rd Qu.       Max.   Global

X.Intercept. -1574.4098   -53.8875    88.4952   472.7282  3092.1466 534.4908

lmhhinc       -151.0306    -7.0538     3.2205    22.3099   120.2753   2.4616

lpop           -76.6700     1.1576     7.2067    20.4788   109.5747  -1.3441

pnhblk        -124.9781    -2.0948    44.5163   100.0885   490.8730  21.1576

punemp        -627.4200  -150.5909   -17.8892    69.6271   752.1507  -5.0966

pvac         -1329.2458     2.5473   165.4452   343.9353  1108.9034 371.6993

ph70         -1028.8902  -161.7810   -43.4011    -8.2491   144.6265 -79.6910

lmhval        -178.5925   -70.3725   -26.7389    -3.7657    89.1748 -45.6676

phnew        -3747.6137  -484.6544    54.6557   734.6135  6434.5611  17.9575

phisp         -313.3416   -24.9975     4.8295   117.2091  1533.6439 -56.3076

Number of data points: 376 

Effective number of parameters (residual: 2traceS – traceS’S): 220.8092 

Effective degrees of freedom (residual: 2traceS – traceS’S): 155.1908 

Sigma (residual: 2traceS – traceS’S): 59.06332 

Effective number of parameters (model: traceS): 178.5045 

Effective degrees of freedom (model: traceS): 197.4955 

Sigma (model: traceS): 52.3567 

Sigma (ML): 37.9452 

AICc (GWR p. 61, eq 2.33; p. 96, eq. 4.21): 4491.91 

AIC (GWR p. 96, eq. 4.22): 3979.926 

Residual sum of squares: 541379.3 

Quasi-global R2: 0.81575

> gwr.b2<-gwr.sel(usarea ~ lmhhinc   + lpop + pnhblk + punemp + pvac  + ph70 + lmhval +phnew + phisp, data = philly2.sp, gweight = gwr.bisquare)

> gwr.fit2<-gwr(usarea ~ lmhhinc   + lpop + pnhblk + punemp + pvac  + ph70 + lmhval +phnew + phisp, data = philly2.sp, bandwidth = gwr.b2, gweight = gwr.bisquare, se.fit=T, hatmatrix=T)

> gwr.fit2

Call:

gwr(formula = usarea ~ lmhhinc + lpop + pnhblk + punemp + pvac + 

    ph70 + lmhval + phnew + phisp, data = philly2.sp, bandwidth = gwr.b2, 

    gweight = gwr.bisquare, hatmatrix = T, se.fit = T)

Kernel function: gwr.bisquare 

Fixed bandwidth: 5092.898 

Summary of GWR coefficient estimates at data points:

                   Min.    1st Qu.     Median    3rd Qu.       Max.   Global

X.Intercept.  -649.3890    -5.7699   134.6249   512.9574  2336.5957 534.4908

lmhhinc       -180.3145    -4.4545     1.7487    13.7554    68.2914   2.4616

lpop           -49.1608     1.2314     6.3430    19.0823    69.7005  -1.3441

pnhblk        -106.4233     1.3658    41.0256    96.5291   285.2134  21.1576

punemp        -397.5988  -143.8982    -6.2685    57.4553   729.4700  -5.0966

pvac          -757.5534     8.8245   209.8576   370.7793   650.3669 371.6993

ph70          -643.0070  -207.9799   -66.3040   -19.8028   142.9682 -79.6910

lmhval        -150.2726   -69.5496   -34.8198    -6.7118   107.7625 -45.6676

phnew        -1844.6086  -418.1211    19.6153   509.9117  7421.2055  17.9575

phisp         -221.0604   -26.5670    -7.5865    84.2566  1418.3152 -56.3076

Number of data points: 376 

Effective number of parameters (residual: 2traceS – traceS’S): 132.4964 

Effective degrees of freedom (residual: 2traceS – traceS’S): 243.5036 

Sigma (residual: 2traceS – traceS’S): 62.2312 

Effective number of parameters (model: traceS): 107.6713 

Effective degrees of freedom (model: traceS): 268.3287 

Sigma (model: traceS): 59.2826 

Sigma (ML): 50.0803 

AICc (GWR p. 61, eq 2.33; p. 96, eq. 4.21): 4316.932 

AIC (GWR p. 96, eq. 4.22): 4117.761 

Residual sum of squares: 943021.6 

Quasi-global R2: 0.6790573

gwr.b3<-gwr.sel(usarea ~ lmhhinc   + lpop + pnhblk + punemp + pvac  + ph70 +

                    lmhval + phnew + phisp, data = philly2.sp, adapt = TRUE)

gwr.fit3<-gwr(usarea ~ lmhhinc   + lpop + pnhblk + punemp + pvac  + ph70 + lmhval +

+                  phnew + phisp, data = philly2.sp, adapt=gwr.b3, se.fit=T, hatmatrix=T)

> gwr.fit3

Call:

gwr(formula = usarea ~ lmhhinc + lpop + pnhblk + punemp + pvac + 

    ph70 + lmhval + phnew + phisp, data = philly2.sp, adapt = gwr.b3, 

    hatmatrix = T, se.fit = T)

Kernel function: gwr.Gauss 

Adaptive quantile: 0.02491844 (about 9 of 376 data points)

Summary of GWR coefficient estimates at data points:

                    Min.     1st Qu.      Median     3rd Qu.        Max.   Global

X.Intercept. -1413.25718     2.04814   150.67770   593.38119  2856.09861 534.4908

lmhhinc        -77.30238    -6.62505     2.08877    20.59832   121.03243   2.4616

lpop           -71.53993     0.32328     6.55222    19.42020    93.59455  -1.3441

pnhblk        -139.33868    -0.35274    39.43998   102.07286   462.87992  21.1576

punemp        -592.27650  -109.64202    -3.93096    63.56270   623.38186  -5.0966

pvac         -1410.12965    11.95427   193.34738   350.39251  1047.77143 371.6993

ph70          -975.65611  -190.62161   -67.38336   -13.17506   137.47857 -79.6910

lmhval        -185.48730   -73.39044   -36.70912    -7.56967    48.91389 -45.6676

phnew        -2570.54553  -577.37945    29.21937   654.40082  4045.23829  17.9575

phisp         -182.91660   -29.72723    -7.23980    65.71058   771.29484 -56.3076

Number of data points: 376 

Effective number of parameters (residual: 2traceS – traceS’S): 177.8408 

Effective degrees of freedom (residual: 2traceS – traceS’S): 198.1592 

Sigma (residual: 2traceS – traceS’S): 54.21695 

Effective number of parameters (model: traceS): 135.2358 

Effective degrees of freedom (model: traceS): 240.7642 

Sigma (model: traceS): 49.18654 

Sigma (ML): 39.35938 

AICc (GWR p. 61, eq 2.33; p. 96, eq. 4.21): 4258.02 

AIC (GWR p. 96, eq. 4.22): 3964.174 

Residual sum of squares: 582484.4 

Quasi-global R2: 0.8017605

> gwr.fit1$bandwidth

[1] 1322.708

> philly2$bwadapt <- gwr.fit3$bandwidth

> tm_shape(philly2, unit = “mi”) +

+    tm_polygons(col = “bwadapt”, style = “quantile”,palette = “Reds”,

+                border.alpha = 0, title = “”) +

+    tm_scale_bar(breaks = c(0, 1, 2), size = 1, position = c(“right”, “bottom”)) +

+    tm_compass(type = “4star”, position = c(“left”, “top”)) +

+    tm_layout(main.title = “GWR bandwidth”,  main.title.size = 0.95, frame = FALSE, legend.outside = TRUE)

First Email to LAPD Office of Inspector General 12.23.21

I have been harassed without provocation or warrant by a crew of Vice detectives out of the Pacific Division. The D2’s name is Edward Acosta. He supervises 2 D1’s and he has employed his own son and the son of one of the D1s he supervises to assist in attacking me. The campaign of terror started in May and has continued until this week. I can present a case to you and supply you with plenty of evidence to prove my claim. They are transphobic. I have been targeted as the result of being transgender. I’m attempting to discern the best way to communicate this information to initiate an investigation with Los Angeles Police Department Internal Affairs.

Thank you,

Barbie