Book Review: Substance Abuse: Circles of Recovery: Self-Help Organizations for Addictions
Bibliographic record
Abstract
Substance Abuse Circles of Recovery: Self-Help Organizations for Addictions. Keith Humphreys. Cambridge (UK): Cambridge University Press; 2004. 228 p. US$25.00 Reviewer rating: Good This is a volume from the International Research Monographs in the Addictions series that presents both clinical and public health applications of biological, behavioural, and statistical addiction research. Keith Humphreys, from the Department of Psychiatry, Stanford University, Stanford, California, has written extensively about self-help groups and outcome research over the past decade. This small book attempts to list, describe, and integrate the literature on all the registered self-help addiction groups worldwide. Reading it is like reading a dictionary: it has interesting, but often unrelated, individual items. It is also a tough read, since there is no consistent theme and the groups described are frequently unconnected, as is common with reference texts. The book's scope is broad and provides a general introduction to numerous addictionrelated self-help groups. Humphreys' goal was to illustrate the range of societal involvement in chemical dependencies, along with professional and lay responses to the worldwide problem of addictions. However, the book sacrifices depth, which it might have achieved if Humphreys had focused on the largest such organization: Alcoholics Anonymous (AA). Certain groups (for example, AA, Blue Cross, Narcotics Anonymous, and Links) see substance abuse as a physical, spiritual, and moral problem. Conversely, others such as Rational Recovery and SMART Recovery, view it as primarily an unhealthy behaviour problem. Global cross-cultural issues also exist, both in the type of intoxicants preferred and in the philosophy of therapy given. For instance, it is assumed that alcoholism is rare in Asian and Semitic populations, owing to genetics and to having close family structures that may make drinking physically unpleasant or unacceptable. That said, these populations are well represented in the use of other addictive drugs, and some individuals within them feel doubly excluded because of their community's disbelief that they could suffer from alcoholism. With regard to alcoholism, high rates of drinking can be found by measuring population consumption levels, but an even more accurate method is to assess the degree of liver cirrhosis (for example, Ireland, Scotland, and Italy, among other countries, have high rates). In most modern cities, however, it is the rule rather than the exception that, although over 10% of the general population abuse alcohol, people with addictions depend on multiple drugs. It is beyond the scope of this review to discuss all the different self-help addiction groups available, but it is sufficient to say that 50% are located in the US and 5% in Canada. Worldwide, AA alone has over 100 000 groups and 2 million members who attend regularly. It is estimated that 3 times this number have some contact with a group, without necessarily joining. What makes self-help groups so popular? Humans tend to gather together, accumulate resources, and solve shared threats. Most group members seek professional help; however, as with most chronic problems, it is not the acute problem that presents the major disability but the chronic, ongoing one. Physicians and self-help groups share something in common-mutual distrust! Some members have had bad experiences with conditioning and behavioural techniques as well as with newer medications that proved later to have abuse potential. …
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.079 | 0.044 |
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".