Holding pattern: an exploratory study of the lived experiences of those on methadone maintenance in Dublin North East.
Bibliographic record
Abstract
According to the European Monitoring Centre for Drugs and Drug Addiction, there are between 1.2 and 1.5 million opiate dependent individuals in the European Union (EMCDDA, 2010) with an estimated 18,136 and 23,576 opiate users resident in Ireland (Kelly et al., 2009). Approximately 11,807 opiate users in Ireland are known to services and are predominantly aged between 25 and 34 years, male, early school leavers, unemployed (Kelly et al., 2009; Carew et al., 2009). In terms of treatment data, records show an increase in both prevalence and incidence rates among 15 to 64 year olds, with 11,538 cases treated in 2007 (Carew et al.2009). One quarter of treatment cases in 2007 had stabilised prior to treatment entry and were on methadone maintenance (Long and Lyons, 2009). However, the chronic relapsing nature of opiate dependency remains evident with more than half of these cases needing more than one treatment intervention (Carew et al., 2009). The researchers utilised a mixed method approach using focus groups with the Client forum representatives of the Special Community Employment schemes, and a series of in- depth interviews with individuals attending the Special Community Employment schemes in the Dublin North East Drug Task Force area.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".