Recovery dialects: A pilot study of stigmatizing and nonstigmatizing label use by individuals in recovery from substance use disorders.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
= 54) used both labels at high rates ("addict": 66.67%; "person with a SUD": 38.89%), though mutually exclusive use was lower ("addict" only: 35.19%, "person with a SUD" only: 7.5%). Common label use settings included mutual-aid recovery meetings, with friends and family, and on social media. Analysis of variance tests found no statistically significant differences between label groups for recovery capital, self-esteem, internalized stigma and shame, flourishing, or length in recovery. Descriptively, participants using only "person with a SUD" had more positive outcomes, although these individuals also had higher levels of internalized shame. Results suggest that language may have only a marginal impact on individuals in recovery, although professionals and the general public should continue to avoid using stigmatizing labels. Additionally, many individuals in recovery have the ability to discern context and setting, switching between positive and negative labels as appropriate. Future research is warranted given these pilot findings and should focus on long-term impacts of self-labeling and internalized stereotypes among individuals in recovery. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 it