Public Stigma Toward Female and Male Opium and Heroin Users. An Experimental Test of Attribution Theory and the Familiarity Hypothesis
Bibliographic record
Abstract
Drug abuse and addiction exist around the world. People addicted to drugs such as opium or heroin often encounter dehumanizing discriminatory behaviors and health-care systems that are reluctant to provide services. Experiencing discrimination often serves as a barrier to receiving help or finding a home or work. Therefore, it is important to better understand the mechanisms that lead to the stigmatization of drug addiction and who is more prone to stigmatizing behaviors. There is also a dearth of research on whether different patterns of stigma exist in men and women. Therefore, this study investigated factors affecting gender-specific stigmatization in the context of drug addiction. In our vignette study ( N Mensample = 320 and N Womensample = 320) in Iran, we experimentally varied signals and signaling events regarding a person with drug addiction (i.e., N Vignettes = 32 per sample), based on Attribution Theory, before assessing stigmatizing cognitions (e.g., blameworthiness), affective responses (e.g., anger), and discriminatory inclinations (e.g., segregation) with the Attribution Questionnaire. We also tested assumptions from the Familiarity Hypothesis by assessing indicators of respondents' familiarity with drug addiction (e.g., knowledge about addiction). Results, for example, show higher stigma if the person used “harder” drugs, displayed aggressive behavior, or had a less controllable drug urge. Self-attributed knowledge about addiction or prior drug use increased some forms of stigma, but diminished others. These findings only partially converged between men and women. We suggest that anti-stigma initiatives should consider information about the stigmatized person, conditions of the addiction, and characteristics of stigmatizers.
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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 | 0.002 | 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 | 0.001 |
| 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".