Are Canadian First Nations Casinos Providing Maximum Benefits? Appraising First Nations Casinos in Ontario, Saskatchewan, and Alberta, 2006-2010(1)
Bibliographic record
Abstract
AbstractTo date a dearth of data has made it difficult to evaluate the success of First Nations casinos in Canada. This paper helps remedy this situation by presenting a three-province overview (Ontario, Saskatchewan and Alberta) of First Nations gaming models. Two key findings are offered that First Nations seeking gaming market entry and provincial officials should genuinely consider. First, while each province has adopted a unique approach to First Nations gaming policy they have each opted to direct substantial revenues out of First Nations communities and into their own treasuries. Second, the evidence suggests that larger gaming properties located nearby a significant market provide more benefits versus smaller properties situated in more isolated areas. The subsequent discussion elaborates each provincial model's revenue generating power, how the revenue in question is being allocated and its corresponding socio-economic impact, whether increased problem gambling and crime have resulted as predicted, while exploring employment trends to determine whether they have developed as anticipated.IntroductionEvaluating the impact of First Nations casinos in Canada has been hampered by a lack of data (cf Cornell, 2008).2 First Nations leaders in several provinces are nevertheless considering investing in reserve casino expansion. There are currently 17 First Nations casinos operating nationally in B.C. (1), Alberta (5), Saskatchewan (6), Manitoba (2) and Ontario (1 for profit; 2 charity). Initially touted as revenue generators that would employ large numbers of Aboriginal employees thus increasing community benefits, provincial premiers in Ontario, Saskatchewan and Alberta echoed the First Nation leadership's positive testimonials to likewise champion reserve casino expansion as a means of improving local First Nations development potential and well-being. Each provincial government chose, however, to execute policies prescribing revenue distribution formulas, restrictions on casino site construction, while most importantly directing casino revenues purportedly earmarked for First Nations communities into provincial treasuries. Despite these setbacks, First Nations leaders in each province remain confident in the reserve casino's potential. Aside from assenting, anecdotal declarations, modest efforts have been directed at exploring each model's exigencies in comparative perspective. This paper represents the first multi-province evaluation of First Nations casinos in Canada and assesses the Ontario, Saskatchewan, and Alberta First Nations gaming models to determine whether First Nations casinos are providing maximum benefits.3 In particular, the following discussion evaluates the three provincial gaming models' revenue generating power, how the revenue is being allocated and its corresponding socio-economic impact, whether increased problem gambling and crime have resulted as projected, while exploring employment trends to determine their impact. This paper unfolds as follows. After a literature review an overview of each provincial First Nations gaming policy is provided followed by a quantitative analysis exploring the aforementioned subjects, and the conclusions.Literature ReviewUnited States Indian nations started utilizing reservation casinos as an economic stimulus in the 1980s. Described as islands of poverty in a sea of wealth (Anderson & Parker, 2008, p. 641), as one researcher has noted, reservation communities [w]ith little or no economy or tax base to fund essential services ... turned to gaming, through self-determination, to generate government revenue needed to fund these services and provide employment for tribal (Schaap, 2010, p. 381). By 2002, over half of all tribal members living in the contiguous 48 states belonged to casino-operating tribes (Evans & Topoleski, 2003) and, in 2008, Indian gaming revenues topped $26.7 billion with 233 Indian tribes operating 411 casinos, bingo halls, and pull-tab operations in 28 states (NIGA, 2009). …
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".