Bibliographic record
Abstract
The Detroit Coalition Against Police Brutality is one of America's first and leading organizations fighting police brutality. The Coalition was founded by educator/activist Gloria House, PhD, and Marge Parsons in 1996, and was led from the late 1990s on by Ron Scott, who passed away in November 2015. Detroit has a long history with police brutality, as Sandra Hines discusses using her own personal experiences. After the city's 1967 Rebellion, precipitated by consistent and pernicious police brutality against African-Americans, Detroit moved quickly to become a predominantly African-American city. Yet, the police force remained dominated by whites. In 1971, the Detroit Police Department created the anti-crime taskforce Stop the Robberies Enjoy Safe Streets (STRESS). In two years, the STRESS unit was involved in the deaths of more than 30 individuals, predominately African-Americans. Ending the STRESS program was one of the campaign promises of Coleman Young, who was elected as the city's first African-American mayor in 1973. While Young worked to integrate the police department, the continuing economic decline of the city meant that major problems remained. As Sandra Hines describes, the immediate impetus for founding the Coalition grew out of the police killing of Malice Green in November 1992, six months after the uprisings in Los Angeles against the acquittal of the police involved in the Rodney King beatings (see Azikiwe, 2006). Since its founding, the Coalition has been active with the Detroit Board of Police Commissioners, which provides civilian oversight of the police department, by attending its regular meetings and bringing issues and incidents of police brutality to the Board. In Scott's obituary, it was argued that the Coalition's work and Scott's advocacy were important factors in Detroit avoiding the kind of anti-police brutality uprisings seen in cities such as Ferguson or Baltimore (Fournier and Dickenson, 2015). Sandra Hines has been active in the Coalition for many years and is currently its President. She hosted a radio show with Ron Scott, Fighting for Justice . For more on the Coalition, see: www.detroitcoalition.org Can you start by describing some of the history of police brutality in Detroit? The Coalition was born to respond to police control over poor and black people. Historically, instead of living by the dictum “to protect and serve,” the police have been there “to command and control.” Over the years, because of where Detroit was located, many black people came from the South to the North.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.098 | 0.023 |
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".