poverty

The Prospect of Rising from Poverty into Self-Sufficiency is Dim

THE AMERICAN DREAM IS VIRTUALLY HISTORY

This is not intended to be a political article.  I’m writing it to open the eyes of those with all political beliefs.  I know the old cliché that money doesn’t buy happiness, but it’s damn hard to be happy if you don’t have any.

Let’s look at a typical single mother with two children ages seven and three.  Her ex-husband is a deadbeat who has skipped town and pays no child support.  She has tried to take legal measures to collect, but such collections are not a priority for the courts.  She is a good mother who loves her kids and shows it.  She doesn’t drink or smoke and doesn’t hit the bars.  She has an occasional date on a weekend for dinner or a movie, but nothing regular.   The picture I’m painting is intentionally of a good person who creates the best possible situation for her children and herself.

As a high school graduate, she finds two jobs.  One is in retail sales for which the national average in $12.20/hour.  The other is as an administrative assistant in a manufacturing facility ten miles from home.  It pays $16.00/hour.  The retail job offers a choice of three shifts.  The office position is 8 to 5.  As you will see, the retail job alone makes her life impossible, so we will give her the higher paying position.  Here is a typical monthly budget for such a scenario.

Income                                                                                                                                                             2773
Expenses:
Taxes (Federal & state income and social security                                                                480
Rent (2BR—2nd lowest in my community)                                                                             725
Groceries (USDA avg. for moderate diet, all meals prepared at home)                            620
Auto insurance (minimum coverage)                                                                                         75
Gasoline (2 tanks)                                                                                                                         100
Utilities (gas, electric, basic cable, basic cell phone)                                                             180
Health insurance (employee share of company plan + optimistic copays)                      260           2440
Remaining after essentials                                                                                                                               333

Unaccounted for:
Medical co-pays, kids’ expenses (lunches, field trips, supplies), clothing, household items, car repairs, and other
AND THE LAST STRAW: CHILD CARE (Avg. for licensed center)
3-year-old (full time)                      600
7-year-old (after school)                 300

Now Mom has some alternatives.

  1. Tough it out, and hope no major expenses arise. Maybe she finds a neighbor who will watch the kids for $40/week. This is risky because there are no enforced standards to this type of care.
  2. Quit the job, and go on welfare.
  3. Take the retail job half-time on second shift. After taxes, this would increase her available cash by $184/week to $517. It also causes her to rarely see her children except on weekends when she is so exhausted she can’t give them the attention they deserve.So let’s say she chooses alternative #1. If nothing goes wrong, she can eke out a life, but let’s look at other circumstances and risks she’s exposed to.
  • She dated a guy for four months a year ago who thinks he owns her. Periodically, he catches her away from home and beats her. Once she was hospitalized.
  • Her car is far from new. Repairs are frequent.
  • Her child care could become undependable, and frequent absences will put her job in jeopardy.
  • The amount nonprofit charities can raise in voluntary contributions is a pebble in a pond compared to the amount needed to right the ship. The only solution I can think of is a radical restructure of our federal tax system (read that as increase for higher incomes) or redeployment of the existing budget (read that as a transfer from defense to education and human services). If you have another one, please let me know.
  • As I read my own article, I guess I have to succumb to what will be perceived as a political statement. I know there are many people who play the system and are undeserving of the assistance available to them. I truly wish we could weed them out. But then I also wish we could weed out those who fraudulently steal millions from pension funds and other sources the middle-class counts on. However, compared to the abusers, there are many-fold who are like my example. Try as they might, they just can’t make it. In Illinois, the median income adjusted for inflation has decreased by 9.5% this century.
  • You can contend that all of us bear these risks, and you are correct. But those of us with greater incomes and some savings have more wiggle room before we reach dire circumstances. We might have to give up some of our toys and maybe even move to a smaller house, but we have many choices before we hit poverty.
  • This makes her a virtual juggler with several balls in the air. If any one of them drops, her act is ruined. She must keep everyone of these facets of her life—job, transportation, child care, violence, housing, kids’ behavior, et al–under control, or her life crumbles.

Now I ask all of you with your six-figure incomes and $200,000 houses and three cars and all the other privileges money brings, tell me how you would handle the situation if you had to trade places with the Mom in our story.  My email address is doug41@comcast.net.

 

 

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IS DATA NECESSARILY PROOF WHEN MEASURING THE HUMAN CONDITION?

INTELLIGENT PEOPLE CAN FOOL THEMSELVES WHEN IT COMES TO DATA

In the fifteen years from 1997 and 2012, the percentage of American homes with at least one computer with Internet access has increased from 18% to 75%.  With this proliferation of access to information has come an increase in demand for data to accompany almost all claims and requests at least in business situations.  This is not an inherently bad phenomenon, but with statistics and other data in the wrong hands, it can be a bit like to handling dynamite.

We live in a data driven time.  All of the stakeholders want to “see the data.”  My mind travels back to my time in manufacturing.  If I had a machine that produced 100 widgets an hour, that would be the baseline.  Then, if someone showed me a machine that would produce 200 widgets an hour, that would get my attention.  The raw materials don’t change, and the same operator is in place.  The only variable is the machine. Depending on its cost, I would have to consider buying that machine.  Cause and effect have been established.

It becomes much more complicated when analyzing data as it applies to the human condition in the nonprofit world.  Not everyone who is charged with decision making based on data understands the difference between correlation and causality.  In fact, I would proffer that most people on both ends of this work in the human services arena are amateurs when it comes to carrying out this responsibility.  The human service professionals are social workers, case managers, and other good people who just want to help those in need.  The evaluators and decision makers, boards and foundations, are often well-intended volunteers trying to make a difference in their spare time.

Foundations and others who hold grant money to give to the most effective programs also want to see data.  Outcome measurements they call them.  I support measuring results as best we can.  However, in measuring outcomes related to humans, we must be careful not to confuse correlation with proven cause and effect.

Let’s say a school system is graduating in four years 70% of the students that enter ninth grade.  It sets a goal to increase that rate to 85% in five years.  The planned solution is to pay teachers on a volunteer basis for two extra hours a day to tutor students who want that service.  Foundation X thinks that is a logical plan, and it grants a half-million dollars to implement the program for five years and promises to consider renewal of the grant if the schools reach their goal.

In five years, the graduation rate is still 70%.  Obviously, the idea failed.  Or did it?  Within those five years the following events occurred:

  • Cuts in government funding to that school system forced the schools to lay off 20% of their teachers. That caused the average class room size to increase from 30 to 37.
  • There was a major downsizing by the town’s largest employer causing many of the parents to lose their jobs. Many of the high school age students had to take minimum wage jobs after school to help out, or worse yet, had to drop out of school to become the bread winner. Or maybe the parent’s loss of a job just put more stress in the home to the point that the student couldn’t concentrate on her studies.
  • A reduction of funding for law enforcement in the city was reduced, and enforcement and punishment for domestic violence offenders and deadbeat dads were no longer priorities.

Each of these events was a factor that caused some number of students to drop out of school.  We don’t know what the tipping point was for each of those students, but it is possible that, without the tutoring program, the graduation rate would have dropped to 60% or lower.

The same logic can be applied in reverse to the measurement of programs that appear to be successful.  And yet, those with the money stand together and applaud and pour more money into the apparent successes, and they stand together and denounce the apparent failures.  All the while they often disregard those collateral circumstances that cause the appearance not to be reality.

Non-profit organizations learn what turns funders on and how to present information accordingly.  I’m not saying they cheat, but they do learn how to play the game.  Those who learn to play the game the best, usually get the money.