Curb Heroin In Plants (C.H.I.P.): Revisiting a Mid-1970s Intervention Into Workplace Heroin Addiction Created and Led by Detroit Autoworkers
Bibliographic record
Abstract
This article analyzes archival records to revisit Curb Heroin In Plants (C.H.I.P.), a public health intervention focusing on drug dependence that was created and led by Detroit, Michigan, autoworkers during the mid-1970s. Responding to widespread heroin use in Detroit auto plants, C.H.I.P. combined methadone maintenance with counseling on and off the job to treat heroin dependence while supporting autoworkers in continuing in employment and family life. Although C.H.I.P. ultimately failed, it was a promising attempt to transcend medical/punitive approaches and treat those with substance use disorder in a nonstigmatizing way, with attention to the workplace dimensions of their disorder and recovery. I argue that revisiting C.H.I.P. speaks to current public health debates about the intersection between the workplace and harmful drug use and how to create effective interventions and policies that are mindful of this intersection. For historians, C.H.I.P. is a valuable example of the crucial role of workplace actors in the early war on drugs and of an early methadone program that was not strongly concerned with crime reduction but incorporated social externalities (specifically job performance) to measure success.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".