Bibliographic record
Abstract
While commercial Indian gaming operations have sprung up only in past quarter century, many tribes have longstanding traditions involving games of chance. (159) Blackfeet tradition recounts how Na'pi (Old Man) brought tribe hoop and arrow game. ... [And how] Blackfeet continue play traditional betting (160) The Blackfeet are not alone, as many tribes have such traditional games. (161) Thus Indian gaming is, in many respects, a new expression of an ancient cultural practice. (162) A. The Early Years Legend has that commercial gaming on Indian reservations in United States began as a response a fire that destroyed two trailers on Oneida Indian reservation in Verona, New York, in 1975. (163) The reservation had neither a fire department nor firefighting equipment, and two oneidas perished in blaze. (164) To prevent such tragedies in future, Oneidas decided to raise money for [their] own fire department ... way all fire departments raise money ... [through b]ingo. (165) The Oneidas launched a bingo game in a double-wide trailer, offering prizes in excess of limits permitted by New York law. (166) The Oneidas maintained that, because they were an Indian nation, they were not bound by state bingo regulations. (167) Tribe members claimed that their right of sovereignty entitled them run their own game and offer a jackpot large enough draw non-Indians and their money-to a place they otherwise might never visit. (168) Subsequently, according one Oneida tribal member, the Seminoles got wind of it (169) and began their own high-stakes bingo game in Hollywood, Florida, in 1979. (170) The Seminole tribe contracted with a non-Indian organization build and manage its bingo hall. (171) The agreement called for managers receive 45% of profits after repayment of a $1 million construction loan. (172) The enterprise was a success, and Seminoles repaid loan in less than six months. (173) As tribal bingo operations grew more successful, states demanded a cut. (174) States unsuccessfully sought extend their laws over [tribal] lands ... prohibit, regulate, and/or tax tribal bingo operations. (175) Whereas district attorney in Madison County, New York, successfully shut down Oneidas' game, Seminoles fought state in courts when Florida authorities tried close Seminoles' bingo hall in 1981. (176) The Seminoles argued that Florida did not have authority prohibit gaming on their reservation, and Fifth Circuit agreed, (177) relying upon Bryan v. Itasca County, in which Supreme Court held that if a state regulates but does not prohibit an activity, may not prohibit that same activity in Indian Country under P.L. 280. (178) Thus, Seminoles secured right run their game and pay out unrestricted prizes. B. Gambling in Connecticut In 1971, Connecticut legalized gambling when, during a fiscal crisis, state government passed legislation sanctioning a state lottery, off-track betting, and horse racing. (179) In 1976, state legislature authorized betting on greyhound racing as well as jai alai, (180) and created a state-run, off-track betting system. (181) Despite state's efforts regulate gambling, Connecticut-based greyhound racing and jai alai operations soon were enmeshed in scandal, and reports of misconduct surfaced frequently. (182) In 1976, in response widespread corruption, state legislature imposed a one-year moratorium on provision of new gambling licenses. (183) Nonetheless, illegal activity continued plague Connecticut gambling. In 1979, government appointed a grand jury investigate betting irregularities at state's three jai alai frontons. (184) The probe led first arrests and convictions of players and bettors for fixing games in forty-five-year history of jai alai in United States. …
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.032 | 0.012 |
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".