Chasing the Dream -- Casinos and Opportunity
Bibliographic record
Abstract
All the North Dakota reservations, and many nationwide, have their casino. It might even have a golf course, a filling station and a restaurant. Or not. Scott Davis, Director of the North Dakota Native American Commission, David Archambault II, Chair of the Standing Rock Sioux, and Kathryn Rand and Steven Light, Co-Directors of the Institute for the Study of Tribal Gaming Law and Policy at the University of North Dakota talk about how Tribal Gaming works, how it helps, and the limits of what it can do. Chasing the Dream: Poverty and Opportunity in America is WNET’s multi-platform public media Initiative that aims to provide a deeper understanding of the impact of poverty on American society: what life is like below the poverty line, its impact on our economic security and on our children, and what has happened to our age-old dream of striving for a better life. We’ll also highlight solutions: what has worked – and what is working to bring people out of poverty – and what lessons we can and must learn for the future. Intro – Funding for this series comes from the JPB Foundation and the Ford Foundation. On many Native American reservations across the country, poverty is a major issue. As part of the “Chasing the Dream” series about poverty and opportunity in the United States, we are looking at reservations and how they try to work on that issue. One effort, one that has had some controversy, is what is known as American Indian Gaming. Bill Thomas has more (research assistance by John Corley). BT: David Archambault the Second is the tribal chair of the Standing Rock Sioux. When he talks about the Standing Rock reservation, he probably sounds like many other tribal leaders around the country. David Archambault: There’s more beauty than anything, and the land is almost untouched, majority of tribal land that exists and a lot of land is used for grazing so you don’t see a lot of farmland unless you go towards the west of the reservation, but what I see, what I experience we have a beautiful river, we have deep grass we have rolling hills, and of course we have the wind. So, All of this is something I cherish I love where I live I love where I’m at But there’s also the hardships that exists – but that’s by no one’s fault but I would say the federal government – over the last century with implementing Indian policy on our tribe -- not only our tribe but all of Indian Country. It wasn’t always good – and the result of it is hardship – We have a high poverty rate, there’s probably 40% poverty rate, 3 times the national average, we have a high rate of unemployment – around 60% unemployment – we have all the symptoms that come with poverty, the dropout rate, all the abuses, drug, physical, mental, sexual abuses exist, so there’s the hardships that we deal with, but at the same time there’s a lot of good, we have our culture, we have our language, we have our environment. BT: Those hardships, though – sometimes they can be pretty hard. And this situation is not new. In a way, it’s almost built in. Reservations tend to be on less desirable lands, tend to be remote, have been whipsawed by changing strategies from the Feds – reservations reduced,land taken away, money put in a trust fund that was criminally bungled, … Not to mention that the people on the reservations were often shocked from disease, coming off of war and sometimes what would now be called ethnic cleansing or genocide, with the official policy at other times being to wipe out not the people but their language and culture. Given all that, it is not much of a surprise that almost all the reservations around the country have outsize poverty rates – for example, let’s look at North Dakota. These figures are from the US Census. The one that’s doing best is Lake Traverse, the Sisseton-Wahpeton Oyate, with about 11,000 people their poverty rate is at 22.6% Next best is Fort Berthold, the MHA Nation, the 3 Affiliated Tribes, up there in oil country -- 23.6% under the poverty line out of 7,116. For Standing Rock, with Dakota and Lakota people, going over North and South Dakota in the center of the state, David Archambault had it right – with about 8300 people, 40.2% are below poverty level income. And for Turtle Mountain, home to Anishinabe, or Ojibwe people, almost in Canada in north central North Dakota, 41.0% out of about 9,000 are classed as in poverty. Of course, there have been a number of efforts to alleviate the poverty – job training, education, agriculture, cultural renewal – most of these with some form of federal support. One idea, though, definitely did not come from the Bureau of Indian Affairs. Here is a hint… SFX: [casino sounds, slot machine pay out] If you are one of the many Americans who gamble, you may recognize the sound of a casino and a slot machine paying out. How did gambling, or gaming to use the more generic and polite term, come to be an economic development strategy for reservations? Kathryn Rand: Tribes are innovators. They've been innovators within the gaming industry itself. BT: That is someone who knows a lot about it. Kathryn Rand: My name is Kathryn Rand. I'm the dean and Floyd B. Sperry professor at the University of North Dakota School of Law and also co-director of the Institute for the Study of Tribal Gaming Law and Policy. Steven Light: I'm Steve Light. I'm a political scientist at the University of North Dakota. I'm co-director of the Institute for the Study of Tribal Gaming Law and Policy. I'm also an associate vice president here. BT: Steve and Kathryn are married, by the way, which makes them good at tag teaming this explanation of some recent history. Kathryn Rand: In the 1970s and 1980s, tribes started experimenting with some high-stakes bingo halls and card rooms on their reservations. As you might guess, those bingo halls and card rooms were operating outside of state regulations, so states tried to shut those down on the reservation. It all came to a head in a US Supreme Court case, California versus Cabazon Band of Mission Indians, back in 1986. The Court held that operating gaming on a reservation was an aspect of tribal sovereignty, and states could not regulate it Steven Light: When Congress got into the act, it passed the Indian Gaming Regulatory Act of 1988, and that piece of legislation set forth some important policy goals to govern Indian gaming and to provide for the regulation at three levels: The tribal level, state level, and the federal level. The main policy goals revolved around promoting tribal self-governance and self-determination and also addressing some of the long-standing socioeconomic deficits on reservations related to poverty and unemployment and the like. BT: Specifically, the act, known as IGRA, required that gaming income be used To fund tribal government To provide for the general welfare To promote economic development. To donate to charity To help fund local government agencies. But here is someone who thinks the most important thing is sort of a side effect of these purposes. Scott Davis: My name is Scott James Davis. My Indian name, Lakota name, is Oshka Tekawa. I am a proud member of the Standing Rock Sioux Tribe, and also a descendant of the Turtle Mountain Band of Chippewa. I serve the governor of our state of North Dakota, as his liaison, serving as a Commissioner for Indian Affairs for the State of North Dakota. BT: Here is what he thinks is important. Scott Davis: But really the biggest and most strongest reason why casinos were created on our reservations is for jobs. It creates jobs. My brother works at a casino. It provides a job for him, his family, it contributes to the economy, the community, so forth. BT: How many jobs? Steve Light says, for each tribe Steven Light: We're talking about two to four hundred jobs, basically, on-reservation for American Indians for tribal casino in North Dakota. BT: And when we talked to North Dakota Indians about their struggles with poverty n general, casino jobs came up: Brenda Kill Small: stepping outside was just too scary for me. I moved back home, and I did start work out at the casino and worked there for, I would say, about a year and about very different jobs. I moved from different jobs within that year. Heather Demaray: Then I would go back and forth between her and my aunt in New Town. I could stay at my aunt's, I stayed there and then eventually I worked at the casino, and I was bar tending in the evening. By then too, my daughter's… Marian DeClay: There was no program, because I messed up the first time with my financial aid and everything. I was working full time at the Desert Diamond Casino down in Tucson. I would work from 11:00 at night to 7:00 in the morning. During the day, my classes will start at 9:00 AM and wouldn't be done until about 3:00. I think that was the part that was just so hard. Steven Sitting Bear : I came out of the military thinking that meant something in the real world, back home. I came home and found out very quickly that a 2.0 GPA at a high school and 4 years honorable service in the Marines didn't really ... Wasn't the job skills that people were looking for. I had found a job at our casino. It was about 6 bucks an hour. I was just happy to have a job. There were struggles that were going on during that time, just trying to make ends meet. I worked there at the casino for 2 and 1/2 years in different departments. I was able to work my way up the ladder a little ways. I realized that if I ever- That glass ceiling, so to speak, right. In sociology and psychology, we talk about this glass ceiling. If you don't have the credential to get beyond it, you're never going to see past it. BT: That was Brenda Kill Small,
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.010 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".