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"Disabled". An over counted minority
- Thread starter MASSDRIVER
- Start date
conarb
Registered User
Brent:What you fail to understand is that it is perfectly legal to discriminate, you just can't discriminate against Suspect classes of people. This is complicated at law becasue there are Suspect Classes, Quasi-suspect classes, and All others, in addition Suspect classes get strict scrutiny, Quasi-suspect classes get Intermediate scrutiny, and All others get Rational basis scrutiny. The disabled came late to the party and are classified in All others entitled to Rational basis scrutiny. The subject then turns to reverse discrimination, every time the law grants special treatment to certain classes of people it deprives others This is nowhere more evident than in college admissions, Bakke made quotas unconstitutional, so the EOC came up with Affirmative Action, in 2003 Justice O'Conner ruled in Grutter v. Bollinmger that while basically unconstitutional the minorities needed 25 more years of special privileges, just this year the Court again reviewed the matter and removed the time constraint saying that Diversity itself was a valuable consideration for all members of society, so diversity didn't just benefit the suspect classes it benefited all. Interestingly through our public educational system young people already see diversity as the ultimate good, I was reading the paper the other day and saw this cartoon about a teenager looking at colleges, note how thrilled she is to see "A happy diverse group of happy laughing friends", I bet she is seeing an Asian, a white, a black, and a person in a wheelchair all sitting on a sunny lawn laughing in complete harmony.
View attachment 946
One of the consequences of giving people special treatment and entitlements is that the entitled may become lazy and obnoxious.View attachment 946
/monthly_2013_11/luann.gif.4333bbcd8202b5301e63d0b79e607550.gif
View attachment 946
One of the consequences of giving people special treatment and entitlements is that the entitled may become lazy and obnoxious.View attachment 946
/monthly_2013_11/luann.gif.4333bbcd8202b5301e63d0b79e607550.gif
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steveray
SAWHORSE
Yes....to some extent in all cases....assuming you are not talking about the structures themselves but the people that build and maintain them.....
MASSDRIVER said:
conarb
Registered User
Jake:Jake said:
I wonder if a cost benefit analysis has ever been done on ADA laws? Obviously there are some good parts that all good people should support, but there are many over-reaching stautes and reglations that even many disabled don't want. As I've said before my biggest objection is the companies, organizations, and individuals who exploit the law and the truly handicapped for their personal financial benefit.
MASSDRIVER
Registered User
And you should.TJacobs said:
Brent
MASSDRIVER
Registered User
That's what this thread is about.TJacobs said:
Brent
ICE
Oh Well
Pretty soon, only criminals will have regular receptacles.JPohling said:
ICE
Oh Well
The ADA lobby won't be satisfied until six months in a wheelchair becomes a rite of passage and the Sierra Nevada mountain range is paved over.
RJJ
Co-Founder
Well Brent I see the point and you have a good debate going. Type on!:-D
mark handler
SAWHORSE
Individuals use the term disability in different contexts; disability is not a single definition. Even Medical personal often refer to the term disability in the physical realm or as a physiological condition requiring treatment or therapy.
As a demographic category, disability is an attribute with which individuals may broadly identify, similar to race or gender. In contrast, certain federal programs narrowly define disability as the impairment or limitation that leads to the need for the program’s benefit such as the Social Security Disability Insurance program’s income support for individuals who are not able “to engage in any substantial gainful activity.” The agencies and organizations that provide benefits to, advocate for, or study these populations, each refer to their targeted group as people with disabilities; but because of the differences in definitions, an individual may be considered to have a disability under one set of criteria but not by another.
Disabilities Affect One-Fifth of All Americans
http://www.census.gov/prod/3/97pubs/cenbr975.pdf
ABOUT 1 IN 5 AMERICANS HAVE some kind of disability, and 1 in 10 have a severe disability. And, with the population aging and the likelihood of having a disability increasing with age, the growth in the number of people with disabilities can be expected to accelerate in the coming decades.
If current trends continue, Americans 65 years old and over will make up 20 percent of the total population by the year 2030 compared with about 12 percent currently. In the October 1994 - January 1995 period, for example, about 16 million of an estimated 31 million seniors age 65 and over reported some level of disability.
As a demographic category, disability is an attribute with which individuals may broadly identify, similar to race or gender. In contrast, certain federal programs narrowly define disability as the impairment or limitation that leads to the need for the program’s benefit such as the Social Security Disability Insurance program’s income support for individuals who are not able “to engage in any substantial gainful activity.” The agencies and organizations that provide benefits to, advocate for, or study these populations, each refer to their targeted group as people with disabilities; but because of the differences in definitions, an individual may be considered to have a disability under one set of criteria but not by another.
Disabilities Affect One-Fifth of All Americans
http://www.census.gov/prod/3/97pubs/cenbr975.pdf
ABOUT 1 IN 5 AMERICANS HAVE some kind of disability, and 1 in 10 have a severe disability. And, with the population aging and the likelihood of having a disability increasing with age, the growth in the number of people with disabilities can be expected to accelerate in the coming decades.
If current trends continue, Americans 65 years old and over will make up 20 percent of the total population by the year 2030 compared with about 12 percent currently. In the October 1994 - January 1995 period, for example, about 16 million of an estimated 31 million seniors age 65 and over reported some level of disability.
mark handler
SAWHORSE
CNSnews "....misinform the public, behind the guise of “news” reporting."
Always consider and scrutinize you sources of information.
Always consider and scrutinize you sources of information.
Last edited by a moderator:
ADAguy
Registered User
Mass, have you "met" Ed yet? You might learn more than a few things from him.
You have touched more than a nerve among many of us.
In some circles you would be viewed as an "anti-".
Then again, dialogue is similar to having another drink; some need just one more and some can walk away.
Is your bottle half empty or half full?
You have touched more than a nerve among many of us.
In some circles you would be viewed as an "anti-".
Then again, dialogue is similar to having another drink; some need just one more and some can walk away.
Is your bottle half empty or half full?
ADAguy
Registered User
Interesting to note the parts of the definitions you chose to omit (smiling!!!)
en•ti•tle•ment
noun\-ˈtī-təl-mənt\: the condition of having a right to have, do, or get something
: the feeling or belief that you deserve to be given something (such as special privileges)
1. The act or process of entitling.
2. The state of being entitled.
: a type of financial help provided by the government for members of a particular group
1wel•fare
noun \ˈwel-ˌfer\
a. Health, happiness, and good fortune; well-being.
b. Prosperity.: a government program for poor or unemployed people that helps pay for their food, housing, medical costs, etc.
en•ti•tle•ment
noun\-ˈtī-təl-mənt\: the condition of having a right to have, do, or get something
: the feeling or belief that you deserve to be given something (such as special privileges)
1. The act or process of entitling.
2. The state of being entitled.
: a type of financial help provided by the government for members of a particular group
1wel•fare
noun \ˈwel-ˌfer\
a. Health, happiness, and good fortune; well-being.
b. Prosperity.: a government program for poor or unemployed people that helps pay for their food, housing, medical costs, etc.
ADAguy
Registered User
Mark,
Thanks again for expanding my interest in your postings.
The Media’s Misinterpretation of Statistics
Scientific research and the media go hand in hand. Without one another, both are severely restricted. For researchers, what good is a ground-breaking discovery if you have no way to get your findings to the general public? The scientific community relies heavily upon the media for this reason.
Firstly let us discuss why are statistics important. Statistics quantify information, and make it more easily understood. They allow a higher level of detail to be portrayed, and add credibility to research. With this in mind, let us look at two statements.
1. Some university students drive to university.
2. On average, 50% of university students drive to university. **
Adding the percentage value transforms the statement from common sense, to something relevant and meaningful. Statistics are an invaluable component in scientific research, and one that must be given considerable thought.
**Disclaimer: This is purely for illustrative purposes, the actual number is likely to be different.
Statistics can be confusing however, and as such it is vital for them to be reported accurately. A complication is that the media will often not fully understand details of the research. Resultantly, it is important that research is presented both accurately, and at a level that can be understood.
This responsibility falls squarely upon the researcher. Given these requirements are fulfilled by researcher, accurate reporting statistics is the responsibility of the media. Journalists hold an important role in communicating to the public, and must ensure they present details accurately.
Often it is not the actual statistics that are debated, but the conclusions made from the research. Scientists are accustomed to making conclusions based on research, but this is a skill less practiced in journalism.
This is the case in the article “Can breastfeeding halt obesity – or is the media misreading the research?”.
A recent study found that 32 percent of babies are obese, a shocking statistic. The original article attributed this to a combination of bad food, and eating solids too early. Several media sources including MSNBC and AOL Health, came to the conclusion that mothers should breastfeed rather than use formula. Whilst the statistics were reported accurately, the resulting conclusions were anything but. Given that the general public is far more likely to see the article from the press than the original study, this is worrying. In this case, misinforming the general public on a large scale is the outcome – obviously undesirable. Or is it?
Political tacticians are not in search of scholarly truth or even simple accuracy. They are looking for ammunition to use in the information wars. Data, information, and knowledge do not have to be true to blast an opponent out of the water.
In my research on the topic, I came across the above quote. It introduces the concept that misreporting statistics or making incorrect conclusions may not be accidental. There are many situations where adjusting conclusions could be done deliberately for personal reasons. For example, if the owner of a newspaper had a family member who was the CEO of a fast food company. Directing the attention away from the bad food causing obesity in babies and using a scapegoat (baby formula) would be beneficial for the newspaper owner. Far-fetched? Maybe, but its definitely something to think about.
Misleading Statistics
Statistics, when used correctly, can be a good tool for looking at trends in large numbers and making correlations between different events. However, sometimes these statistics are misinterpreted, misanalyzed, or just plain wrong.
Examples of different types of ways to manipulate statistics is given in Misleading Statistics: faulty statistics, bad sampling, Unfair poll questions, statistics that are true but misleading, ranking statistics, qualifiers on statistics, and percentages. These are outlined below:
• Faulty statistics: Statistics can often be fabricated out of thin air. Fabricated statistics are harder to see through than fabricated statements, since statistics command more authority than simple statements.
For example, saying that "61% of all Americans are obese" seems less suspicious than saying "most Americans are obese."
• Bad sampling: Bad sampling is simply sampling too few people, or sampling people who are atypical of the general population. If a television show asks viewers to call in and give a response to a poll, the people who bother to telephone in, and more generally the people who are watching the show might be inclined to answer one way or the other.
• Unfair poll questions: Poll questions may be worded differently in order to create an impression on the voter.
An example from Misleading Statistics claims that there could be two poll questions, "Do you feel you should be taxed so some people can get paid for staying home and doing nothing?" and "Do you think the government should help people who are unable to find work?" Both questions deal with taxes, but the first question is more likely to get more "no" answers than the second question.
• Statistics that are true but misleading: Statisticians can always "select" the data they wish to present in order to mislead the readers. For example, in an election one candidate's supporter claimed that employment was up when their candidate was in office. The opposing party claimed that unemployment was up when their candidate was in often. Both statements were true, since the population had increased during the candidate's time in office, meaning that the number of both employed and unemployed people had risen.
• Ranking statistics: The problem with ranking statistics is that it is dependent on how you split up the items you are ranking. In an example from Misleading Statistics diabetes is listed as the third leading cause of death in the United States -- but is cancer considered one disease, or many diseases based on its nature (lung cancer, breast cancer, colon cancer, etc.)?
• Qualifiers on Statistics: By adding qualifiers to statistics, it makes them seem as if they are something they are not.
The brown bear is certainly a large animal, but not the largest in the world. However, if we say that the brown bear is the largest land predator in the world, then that statement is true, and it makes the brown bear's size seem more impressive.
• Percentages: Statisticians can switch between numbers and percentages based on which looks more impressive:
if a factory of 100,000 people fires 10,000 people, a newspaper might report that 10,000 people were fired. However, if a factory of 100 people fires 10 people, that same newspaper might report that 10% of all workers were fired.
Misleading Statistics also discusses how to avoid being misled by statistics. One strategy is to take a step back, and look at how the statistic could have been reworded or changed to make it seem misleading. Another strategy is to consider the group who is presenting the statistics: do they have a reason to be biased one way or another, or are they neutral?
Thanks again for expanding my interest in your postings.
The Media’s Misinterpretation of Statistics
Scientific research and the media go hand in hand. Without one another, both are severely restricted. For researchers, what good is a ground-breaking discovery if you have no way to get your findings to the general public? The scientific community relies heavily upon the media for this reason.
Firstly let us discuss why are statistics important. Statistics quantify information, and make it more easily understood. They allow a higher level of detail to be portrayed, and add credibility to research. With this in mind, let us look at two statements.
1. Some university students drive to university.
2. On average, 50% of university students drive to university. **
Adding the percentage value transforms the statement from common sense, to something relevant and meaningful. Statistics are an invaluable component in scientific research, and one that must be given considerable thought.
**Disclaimer: This is purely for illustrative purposes, the actual number is likely to be different.
Statistics can be confusing however, and as such it is vital for them to be reported accurately. A complication is that the media will often not fully understand details of the research. Resultantly, it is important that research is presented both accurately, and at a level that can be understood.
This responsibility falls squarely upon the researcher. Given these requirements are fulfilled by researcher, accurate reporting statistics is the responsibility of the media. Journalists hold an important role in communicating to the public, and must ensure they present details accurately.
Often it is not the actual statistics that are debated, but the conclusions made from the research. Scientists are accustomed to making conclusions based on research, but this is a skill less practiced in journalism.
This is the case in the article “Can breastfeeding halt obesity – or is the media misreading the research?”.
A recent study found that 32 percent of babies are obese, a shocking statistic. The original article attributed this to a combination of bad food, and eating solids too early. Several media sources including MSNBC and AOL Health, came to the conclusion that mothers should breastfeed rather than use formula. Whilst the statistics were reported accurately, the resulting conclusions were anything but. Given that the general public is far more likely to see the article from the press than the original study, this is worrying. In this case, misinforming the general public on a large scale is the outcome – obviously undesirable. Or is it?
Political tacticians are not in search of scholarly truth or even simple accuracy. They are looking for ammunition to use in the information wars. Data, information, and knowledge do not have to be true to blast an opponent out of the water.
In my research on the topic, I came across the above quote. It introduces the concept that misreporting statistics or making incorrect conclusions may not be accidental. There are many situations where adjusting conclusions could be done deliberately for personal reasons. For example, if the owner of a newspaper had a family member who was the CEO of a fast food company. Directing the attention away from the bad food causing obesity in babies and using a scapegoat (baby formula) would be beneficial for the newspaper owner. Far-fetched? Maybe, but its definitely something to think about.
Misleading Statistics
Statistics, when used correctly, can be a good tool for looking at trends in large numbers and making correlations between different events. However, sometimes these statistics are misinterpreted, misanalyzed, or just plain wrong.
Examples of different types of ways to manipulate statistics is given in Misleading Statistics: faulty statistics, bad sampling, Unfair poll questions, statistics that are true but misleading, ranking statistics, qualifiers on statistics, and percentages. These are outlined below:
• Faulty statistics: Statistics can often be fabricated out of thin air. Fabricated statistics are harder to see through than fabricated statements, since statistics command more authority than simple statements.
For example, saying that "61% of all Americans are obese" seems less suspicious than saying "most Americans are obese."
• Bad sampling: Bad sampling is simply sampling too few people, or sampling people who are atypical of the general population. If a television show asks viewers to call in and give a response to a poll, the people who bother to telephone in, and more generally the people who are watching the show might be inclined to answer one way or the other.
• Unfair poll questions: Poll questions may be worded differently in order to create an impression on the voter.
An example from Misleading Statistics claims that there could be two poll questions, "Do you feel you should be taxed so some people can get paid for staying home and doing nothing?" and "Do you think the government should help people who are unable to find work?" Both questions deal with taxes, but the first question is more likely to get more "no" answers than the second question.
• Statistics that are true but misleading: Statisticians can always "select" the data they wish to present in order to mislead the readers. For example, in an election one candidate's supporter claimed that employment was up when their candidate was in office. The opposing party claimed that unemployment was up when their candidate was in often. Both statements were true, since the population had increased during the candidate's time in office, meaning that the number of both employed and unemployed people had risen.
• Ranking statistics: The problem with ranking statistics is that it is dependent on how you split up the items you are ranking. In an example from Misleading Statistics diabetes is listed as the third leading cause of death in the United States -- but is cancer considered one disease, or many diseases based on its nature (lung cancer, breast cancer, colon cancer, etc.)?
• Qualifiers on Statistics: By adding qualifiers to statistics, it makes them seem as if they are something they are not.
The brown bear is certainly a large animal, but not the largest in the world. However, if we say that the brown bear is the largest land predator in the world, then that statement is true, and it makes the brown bear's size seem more impressive.
• Percentages: Statisticians can switch between numbers and percentages based on which looks more impressive:
if a factory of 100,000 people fires 10,000 people, a newspaper might report that 10,000 people were fired. However, if a factory of 100 people fires 10 people, that same newspaper might report that 10% of all workers were fired.
Misleading Statistics also discusses how to avoid being misled by statistics. One strategy is to take a step back, and look at how the statistic could have been reworded or changed to make it seem misleading. Another strategy is to consider the group who is presenting the statistics: do they have a reason to be biased one way or another, or are they neutral?
MASSDRIVER
Registered User
Just quickly, want to expand tonight.
I agree you have to be careful with stats. But raw numbers are useful. Thanks to mark and ADAGUY for dialog.
But briefly, on this point, my simple contention is there are far less disabled that actually NEED architectural assistance than is thought, or more concisely, born out of statistics. The notion that even 20% of our population is so disabled that they require special Ada construction is absurd. There is the huge number of disabled, then are are subsets to which there's abuse of the system. And down there somewhere is the actual number that truly benifit, or more accurately require architect help.
Brent
I agree you have to be careful with stats. But raw numbers are useful. Thanks to mark and ADAGUY for dialog.
But briefly, on this point, my simple contention is there are far less disabled that actually NEED architectural assistance than is thought, or more concisely, born out of statistics. The notion that even 20% of our population is so disabled that they require special Ada construction is absurd. There is the huge number of disabled, then are are subsets to which there's abuse of the system. And down there somewhere is the actual number that truly benifit, or more accurately require architect help.
Brent
There will always be people who game the system and abuse it to their benefit. Unfortunately we should not let that stop us from providing improved accessibility from those who genuinely need this type of assistance. What % of the population being disabled would you determine is the tipping point that you would then feel comfortable providing these types of improvements?
Not even considering the individuals that were born with the types of disabilities that would benefit from these codes/laws, or were involved in accidents or incurred diseases etc, being born and raised in a military town I feel compelled to provide these types of improvements to the built environment solely for the benefit for our injured soldiers. If someone has sacrificed their limbs in order for me to remain free I owe it to them to make sure they dont have to pee themselves.
Not even considering the individuals that were born with the types of disabilities that would benefit from these codes/laws, or were involved in accidents or incurred diseases etc, being born and raised in a military town I feel compelled to provide these types of improvements to the built environment solely for the benefit for our injured soldiers. If someone has sacrificed their limbs in order for me to remain free I owe it to them to make sure they dont have to pee themselves.
steveray
SAWHORSE
Not to even mention the increase that is coming from the aging baby boomers......(No offense!) We might actually be ahead of the curve....
mtlogcabin
SAWHORSE
Wel´fare`
| n. | 1. | Well-doing or well-being in any respect; the enjoyment of health and the common blessings of life; exemption from any evil or calamity; prosperity; happiness.How to study for the people's welfare. Pros`per´i`ty
Amazing how in 100 years a definition can change from individual achievements to a government provided program The above definitions are from Websters 1913 edition |
Mac
Gold Member
The ADA's forerunner legislation was first passed in 1973. The era of the WW2 generation. A time when other equality laws were being approved.
Kwitcher bellyachin' , do your job, and hope you never need the turning radius, lever doorknob, or breathing apparatus.
Kwitcher bellyachin' , do your job, and hope you never need the turning radius, lever doorknob, or breathing apparatus.
MASSDRIVER
Registered User
No.Mac said:
Brent