The 1995 Marijuana Rescheduling Petition

Can We Generalize About an Average Marijuana User?


Gabriel Nahas has unequivocally stated for the record that, in his opinion, scientific evidence supports "stricter enforcement of drug laws including those aimed at discouraging the use of marihuana . . ."(33)

Social science, in fact, is based on percentage plays and probability. Justice in the United States, however, is not. We do not engage in preventive detention in this country; we do not hold people in prison because we believe they are likely to commit some crime in the future, nor should we criminalize adult marijuana users because a small percentage of them are at risk or susceptible to the use of dangerous drugs. It becomes an even further stretch of logic to suggest that the criminalization of adult marijuana use is an acceptable educational and prevention tool in discouraging teenage use of any drug, an especially ironic policy considering the complete prohibition of marijuana creates an illegal market which virtually guarantees teenage availability.

Many contemporary defenses of existing U.S. marijuana policy rest on the assumption that marijuana use is always symptomatic of other psychological, emotional, or behavioral problems, that is that use is always abuse. However there has never been sufficient evidence to support such a generalization, nor is there today.

The question for analysis is whether acute or chronic use of marijuana produces behavioral problems that pose a threat to public, as contrasted with individual, health. The relation of marijuana use to other drug use has been discussed above. As discussed in section 4 above, there is a considerable population of 'marijuana only' drug users in he United States. Has research provided any basis for generalizing about this group?

Usually this question is only half-answered. Samples of marijuana users are studied by different researchers, and reports of similar findings appear to validate the generalization that marijuana use has some negative, apparently harmful effect on all individual users. For example, a study was conducted in 1983 - 84 on the "Demographic and Health Characteristics of Heavy Marijuana Smokers in Los Angeles County" as part of Tashkin's ongoing research on the respiratory and pulmonary effects of marijuana use (discussed in section 2). The abstract reports their findings that:

"The demographic, life-style, and self-reported health characteristics of a convenience sample of 207 male and 70 female non-Hispanic White, heavy marijuana users in Los Angeles County were compared with those of more representative county and national samples. Consistent with other researchers' findings, heavy marijuana users were found to differ significantly in living arrangements, job stability, and income. Heavy marijuana users did not differ in completed education, self-reported physical health, or use of alcohol and cigarettes. Heavy marijuana users were less likely to be married than nonusers, but reported the same number of close friends with whom they interacted more frequently than same-aged comparison groups. Our findings suggest that heavy marijuana uses are not homogeneous, and that female users differ significantly from male users."(34) (emphasis added)

Advocates could quote selectively from this abstract to support fundamentally different assertions, that heavy marijuana use is connected with job and income difficulties, or that there are no universal traits that can be associated with heavy marijuana use. Subjects for the study responded to advertisements. Perhaps heavy marijuana users with stable jobs and high incomes found it "inconvenient" to respond? Certainly the authors of the study took such a possibility into consideration, but reviews seldom include such technical qualifications or nuances.

It is relatively easy to mis-cite or misquote scientific research, and one of the first clarification's to be ignored involve the limitations of the data and the theoretical construct which provides whatever meaning the data might have. Scientific reasoning requires the testing of predictive hypotheses to validate or reject assertions.

 

 
 
 
  
 
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