RESOURCES AVAILABLE TO PEOPLE WHO USE DRUGS: A CASE STUDY OF TUCSON AND COMPARED CITIES
Bibliographic record
Abstract
People who use drugs are inherently marginalized due to the stigmatization they experience for their habits. At the same time, drug use is prevalent across many demographics, affecting any and all types of people. People’s vulnerability increases after prolonged drug use, when others view them as “addicts” rather than an individual struggling with substance use disorder. It is important to provide people who use drugs with a variety of resources to help them meet their needs in this challenging context. In this paper, I define a list of basic needs that people who use drugs might need help meeting. The needs identified are human rights (including housing, food security and employment), harm reduction, destigmatized health care (including mental health care), legal care, and social needs. Then, I conduct two case studies to investigate what public resources are available to meet these basic needs in Tucson, Arizona and Vancouver, Canada. Next, I compare and contrast the resources provided in these two cities, in order to identify the different government operated and privately organized resources available to the residents of the cities. This identification will highlight what resources work well and provide ideas for future resources that Tucson can provide. Finally, I include recommendations of what can be done to improve the resources that Tucson has to offer, as well as what can be done to maintain some polices created during the COVID-19 pandemic that came to provide vital resources to people who use drugs.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".