The lottery is an old hot topic of controversy with a new surge of debate. With the addition of North Carolina's lottery and the impending implementation of video lotteries, supporters and critics are, once again, suiting up for battle over our nations lotteries and laws. But outside of the active contributors to this conflict, what are the views of our nation regarding the lottery? For the most part, pretty positive. How can you not be, when the lottery takes all that green and turns into read...as in books and other supplies for education. After all, that is the most popular pitch for buying a lottery ticket and supporting the lottery's establishment in a state. In fact, according to The New York Times, most people believe the majority of lottery dollars go to education and that most of the cost of education is covered by lottery dollars. With state lottery slogans like “Big Fun, Bright Futures” and “Raising billions to educate millions,” who's to blame for these beliefs. Below is a video of one such advertisement.

Linked here is The New York Times article that addresses the misconception that the lottery heavily profits the education system: For Schools, Lottery Payoffs Fall Short of Promises. (Most of the facts and sources in this post are from this article, however here is another “Lottery Fact Sheet.”)

The original form of the lottery started in the 1700's and was used to fund different social programs, bridges, roads, and the Continental Army. Now a days, there are thousands of different lottery games you can play with the cost of a ticket going as high as $50 dollars. You can find websites with lottery predictions or you can even be a professional lottery player.

Forty two states, plus the district, have lotteries. Twenty three of these states have dedicated funds to education. However, all lottery sourced money for education only amounts to “between one and five percent of the total revenue for K-12 education.”

Last year the lottery earned 56 billion and returned 17 billion to the state government. 460 million goes towards advertising which is one of the largest ad budgets of any marketer. Lottery officials say that since the induction of the first modern lottery, 234 billion dollars have gone toward state coffers. The majority of sales has to go back into the lottery just to sustain the games.

Here is a map showing the states who contribute at least 30% of their profits to education. One must note that some states put their lottery dollars directly into the general pot, and can't report exactly how many lottery dollars go directly to education.

A bad habit that is developing in certain states is the substitution of general funds for education with lottery dollars. So instead of additional money going towards education when the lottery does well, the education budget gains nothing, but the states general funds give less to meet the same mark. In fact, in Nebraska, they actually transferred lottery dollars out of education and into the general funds to make up for a deficit.

Lottery officials say that they are catching most of the flack for decisions that have nothing to do with the lottery, but are, instead, in the hands of the state legislature who decide what to do with the lottery dollars they receive. “Our job is to raise money for the things the legislators want,” said Clint Harris, director of the Minnesota lottery. “We don’t have any control over what happens to the money.”

The New York lottery director, Gardner Gurney, says, in defense of his percentage statistics, “Too much of the focus is on percentages. My focus is on dollars. You can't spend percentages.” In 2000, New York State kept 38 percent of its lottery revenue for education. That share has dropped to 32 percent, but the dollar amount rose from $1.3 billion in 2000 to $2.2 billion last year, as reported by the NY Times.

Time and again the lottery argument comes back to money for education. According the lottery promoters, people are spending their money on tickets, it's just a matter of whose state they are going to spend their money in. Then to pull a few heart strings, they mention all the kids in their home state who are watching those dollars go to other kids' educations. However, taking a closer look at the facts makes it look like the only thing profiting from the lottery is the lottery. After all, we all know that you have a better chance of being struck by lightning twice than winning the lottery. Or do we? I guess the people standing in line for lottery tickets aren't all decked out in rubber.

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NPR ran a story on Monday’s Morning Edition entitled “Security Officials Seek to Block Some Online Maps”. The story centered around local government officials refusing to release electronic maps of what they call “critical infrastructure,” such as water mains and fire hydrants. Specifically the story of Steven Whitaker’s futile quest to obtain infrastructure data from the Greenwich, CT local GIS repository. As part of the story NPR came by to ask my opinion on the matter because of our history of creating security concerns using open source data.

The story has a nice quote of me saying it was an impossible task to try and control all the geodata out there and who has access to it. The part that did not air is that no one even knows what data is accessible and not accessible to the public. While we do have a good index and census of most of the web pages that exist, we have much less understanding of the databases including geospatial databases connected to the Web (often called the Deep Web). The indexes run by Google and others do a great job finding web pages but databases are a different game. A Cal Berkley study by Bergman found that, “the deep web consists of about 91,000 terabytes. By contrast, the surface web, which is easily reached by search engines, is only about 167 terabytes.” While it is uncertain how much of this data is geospatial in nature it is fair to assume it is a considerable amount of data that we largely have little clue about. Often times government agencies do not even realize what data they have online available to the public, and we definitely do not have a comprehensive way to understand the entire universe of geospatial data. What raised so much alarm with our original research were the authorities realizing that that the data was available open source. Everyone clamored the work should be classified, but the source data is all still out there hidden in myriad local, state, federal and NGO data repositories. This begs the question, how are we going to control a world of data that we have so little comprehension of?

In order to move towards greater security I believe we actually need to open up more so that the entirety of geospatial data can be indexed. We will have no true idea as to what geospatial data available to the public is potentially dangerous until know what is out there. The move towards making KML an OGC standard is a great first step as a standard geospatial data format for the Web. Although KML natively is geared towards providing a geographic framework for text, html, pictures etc., and not structured information like databases. We’ve been working on changing that by ensuring a mechanism exists by which to include feature attribute data in the schema tag of KML . Some of this work has carried over into KML 2.2 as “extended data“.

Once you begin to index the geospatial data out there you are in a much better position to have a logical debate about what data is a security threat and what data contributes to the public good. For instance you may want to know where there have been hazardous pipeline accidents, but not divulge where critical pipeline routing junctures are. By opening up geospatial data, not only do we have a foundation to better insure dangerous data stays out of the hands of bad guys, but we also have the positive externality of a whole wealth of data being made available to the public to solve a wide range of problems.

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In conjunction with this morning’s social media news release announcing we have reached 2500 sets of data on GeoCommons, we also created a short podcast to expand on some details. Sean discusses the exponential power of each new data set added to GeoCommons. He also provides some insights into what may be next for GeoCommons.

If you prefer to download the podcast, please visit media.libsyn.com/media/geoliv/GeoCommons2500podcast3.wav.

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Dealing with Data Accuracy in the GeoWeb: The Day China Annexed Taiwan

One of big gremlins in Geography that often gets over looked is data accuracy. On the surface data accuracy and validation is a pretty dull topic, but when data is wrong or controversial the repercussions can be huge. Google Earth has been a lightning rod for much of the controversy, especially when it comes to the definition of borders between countries. A border controversy in Chile over inaccurate data in Google Earth created a large media stir as did a disagreement between India and Pakistan over the border in the Kashmir region. Interestingly Google outsources the whole volatile issues of borders to Europa Technologies who “supply the international borders, national borders, coastlines, airports and places data featured in Google Earth.” When you have 250 million downloads it is hard for Google Earth to not be a lightning rod, and the truth is there are data accuracy issues all across the GeoWeb and traditional GIS.

GIS has a long history of tackling issues of data accuracy and have created a set of standards like “National Standard for Spatial Data Accuracy” as part of official FGDC metadata. While these standards worked for dealing with data accuracy in traditional GIS, are they sufficient or appropriate for the GeoWeb. Further are there capabilities emerging in the GeoWeb that could help make the entire world of geographic data more accurate. OpenStreetMaps has made a strong case for “crowdsourcing” creating more accurate and timely maps (if not more complete) than tradition GIS approaches. Is there potential in using crowdsourcing to make all geographic data more accurate and timely. Is there a possible symbiotic relationship with existing metadata standards to harness the historical diligence of GIS metadata with the real time responsiveness of crowdsourcing?

I think part of making this leap is recognizing that there is a need for it. Just because geographic data has official metadata and comes from an official source does not mean that it is accurate or current. Take Mikel Maron’s well documented example of a New Orleans bridge destroyed by Hurricane Katrina but remaining as a geographic entity in NAVTEQ and TeleAtlas official datasets (as exposed through Google and Yahoo maps). We recently came across a similar example on GeoCommons. An open source data set of official country boundaries for China released by a large GIS vendor for 2006 included Taiwan as part of China.

Looking at the 2002 dataset Taiwan was not included as a province of China:

Either it is a mistake or the data provider is following the claim by the People’s Republic of China that Taiwan belongs to China. Google has come under pressure for recognizing Taiwan as a province of China, so there is a case to be made.

Politics aside data accuracy and timeliness is a gremlin that is going to plague all parties in the geospatial space be they GeoWeb, GIS, or increasingly a fusion of the two. My question is in the fusion of the two are their opportunities to help both sides out. OpenStreetMaps has presented an approach for increasing the timeliness and relevance of geographic data through crowdsourcing, but the commercial data providers often quip about spatial accuracy and completeness. That said the number of times I’ve used those data sets and been sent down a road that does not exist or sent to a point of interest (POI) that is mislocated is far from rare.

TomTom has been one of the more proactive vendors along these lines allowing users to correct mistakes they find in directions and POI s. Their acquisition of TeleAtlas is a strong indicator of the direction this all takes, and is only further reinforced by Nokia’s acquisition of NAVTEQ. As GIS and the GeoWeb further converge can the crowd help make the world of geospatial data richer, more accurate and more timely? OpenStreetMaps and TomTom have show it can work and reap huge benefits for streets and POI’s, but what other varieties for data or analysis will work? What is next?

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On October 2nd, one of the most emailed New York Times articles in the United States was an op-ed highlighting several coinciding, racially-charged events. These included the slandering of a black female executive for the Knicks, the beating of a popular female Evangelical minister by her husband, the most recent arrest of O.J. Simpson, and, finally, the Jena 6 “miscarriage of justice.”

The article also broaches the gross discrepancies in the rate of black male incarceration compared to white male incarceration in the the United States and looks to uncover the causes behind our penal system's gibbous population. As of June 2006, there were 2,245,189 prisoners behind state and federal bars. The incarceration rate of black men was 4,789 for every 100,000 black males in the population compared to the 736 per 100,000 white males.

Just for reference, a quick international comparison: South Africa under apartheid in 1993, imprisoned 851 black males per 100,000 black males in the populous. The United States (under George Bush) in 2006, imprisoned 4,789 black males per 100,000 black males in the population.

Below are maps heat sourcing the state prisons' population composition.

White Male Incarceration

Black Male Incarceration

Here is a link to the chart with full numeric values of incarceration by race in each state prison: chart

The states with the largest discrepancies: Iowa: White Males 159 Black Males 2818 Difference 2659. DC: White Males 87 Black Males 2720 Difference 2633. Connecticut: White Males 139 Black Males 2296 Difference 2157. Pennsylvania: White Males 108 Black Males 1826 Difference 1718. New Jersey: White Males 115 Black Males 1526 Difference 1411. Minnesota: White Males 59 Black Males 1383 Difference 1324. Illinois: White Males 98 Black Males 1395 Difference 1297.

The states with the least discrepancies: (still twice as many black males as white males) Hawaii: White Males 219 Black Males 579 Difference 360 Vermont: White Males 178 Black Males 451 Difference 273

Rockefeller

As Paul Smith said, “The level of crime and the levels of inequality in a society go hand in hand, statistically you are more likely to commit crime the more oppressed you are.”

Many sources will say the direct cause of our unbalanced prison population is the ineffective laws currently governing drug apprehensions. The total number of people imprisoned in the United States in 1980 is just over the number of people currently imprisoned for only drug offenses. “A major reason for the overflow of African American inmates in New York State prisons is the so-called 'Rockefeller Drug Laws,' enacted in 1973. They require judges to sentence even a first-time offender to a minimum of 15 years in prison for selling two ounces of narcotics.”

These current drug laws are largely considered to be harsh, naive, and ineffective money drains. The New York State Corrections Commissioner, Thomas A. Coughlin, III, says “...the punitive effect of the Rockefeller drug laws, as well as the rigidity of the second felony offender laws, do not deter, they do not lessen, nor do they cure drug addiction. Instead, as far as prisons are being filled with low-level drug offenders, more street level sellers and abusers appear to take the place of those individuals who get caught up in the criminal justice system.”

A Heat Map of Drug Use in the United States

Unemployment

An alarming effect of the deluge of black American men incarcerated since the enactment of the current drug laws, is that upon release, these men are considered mostly unemployable. Employment discrimination is prevalent enough without adding a criminal record to render a black man undesirable for hire. According to the Community Service Society, “The Wall Street Journal reported on a study that showed white men with a criminal record have a better chance of being asked back after a first job interview than black men without a record.” Not to mention the fact that they have already lost the right to vote (“Thirteen percent of the black adult male population has lost the right to vote because of felony disenfranchisement laws.” Human Rights Watch and the Sentencing Project, Losing the Vote.)

Having a criminal record doesn't just bar you from high level, hard to attain jobs; in places like New York, it eliminates your ability to be employed in occupations such a as a licensed plumber or barber. Furthermore, these restrictions are not modified in accordance with the degree or type of crime, they fall across the board, firmly tying the hands of many released felons.

A map of unemployment rates in the United States

Family Structure

What's clear is that there is a devastating and ever increasing disparity in our penal system's racial composition. What is unclear is why that is. There is strong support for the idea that our nation's crippling drug laws are the culprit, however, The New York Times article spawning this blog states that the obvious—but ignored—reason is the increasing failure in African American families due to male/female dissension. According to the article, the abuse of black females is leading to the disintegration of a healthy, prolific family structure. Then there is the all encompassing and all so vague summary that “Although racial bias may play a role in individual cases, most researchers believe racial disparities in the criminal justice system are primarily the result of indirect discrimination; the impact of race-linked (e.g. poverty, education, neighborhood of arrest) disadvantages compounded through out the criminal justice processing system; specific 'social structural contexts;' and such legally relevant race neutral variables as the existence of prior records,” provided by David Cole.

So is it the drug laws, pure and blind racism, familial dysfunction, indirect discriminations, or misfiring drug laws? Probably all of the above. The more important question; what can be done?

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