Perceived barriers to identity transformation for people who are prescribed methadone
Bibliographic record
Abstract
Resolving identity issues and transforming one's identity from ‘user’ to ex-‘user’ is not an easy process in early recovery because the individual might still be discovering their world as a ‘non-user’. This, however, might pose some additional unique difficulty for marginalized individuals such as those who are prescribed methadone. This difficulty might be attributed to the dependence-forming nature unique to methadone maintenance treatment (MMT). Testimonials regarding the experiences from people prescribed methadone commonly share issues of inconvenience, fear of breach of confidentiality, inflexible lifestyle adjustments associated with picking up one's prescription, and a feeling of not being considered normal. The internalized, professional and societal stigma associated to those who are prescribed methadone forces many to remain in the closet, which makes cultivating a new identity difficult. This article reviews the literature pertaining to identity transformation, to examine the unique transformational process experienced by individuals enrolled in MMT. This article will combine qualitative studies exploring the experiences of methadone maintenance recipients and explore the perceived barriers faced by this population in achieving a preferred identity transformation.
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.
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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".