Discussion and Results Chapter: Marijuana Is a Gateway Drug That Leads

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Marijuana Is a Gateway Drug That Leads to the Use of Other Drugs

One of the most hotly-disputed claims in the media is the notion that marijuana is a 'gateway' drug that leads to further drug abuse. There is strong statistical support for this idea: "a person who smokes marijuana is more than 104 times more likely to use cocaine than a person who never tries pot, according to the National Institute on Drug Abuse" (Szalavitz 2013). Not only is there a correlation between hard drug use and marijuana -- the marijuana use usually proceeds the hard drug use in terms of the 'time order' of the series of events.

The counter to this argument is that hard drug users may be more likely to use marijuana than members of the average population because of the factors that drive them to their addiction (spanning from poverty to psychological problems to genetic tendencies). However, is not the marijuana that 'causes' the addiction to hard drugs; rather a person who does hard drugs is more likely to have tried marijuana. Proponents of marijuana legalization states that there is considerable evidence that other variables affect a person's likelihood to use drugs and the relationship between the two variables can be explained by other factors. "Hell's Angels motorcycle gang members are probably more 104 times more likely to have ridden a bicycle as a kid than those who don't become Hell's Angels, but that doesn't mean that riding a two-wheeler is a 'gateway' to joining a motorcycle gang. It simply means that most people ride bikes and the kind of people who don't are highly unlikely to ever ride a motorcycle" (Szalavitz 2013).

Even if there was no marijuana, hard drug addicts would still likely try hard drugs; there is nothing unique about the properties of marijuana that make it particularly dangerous. There is also no covariation: the phenomena do not vary together in equal measure -- someone who smokes a great deal of pot will not necessarily use the same amount of cocaine. Cocaine users are simply more likely to have tried marijuana (along with other, less socially stigmatized drugs) before moving on to the 'hard stuff.'


Szalavitz, M. (2010). Marijuana as a gateway drug: The myth that will not die. Time Magazine.

Retrieved: http://healthland.time.com/2010/10/29/marijuna-as-a-gateway-drug-the-myth-that-will-not-die/

In describing different approaches to the time dimension, criminologist Lawrence Sherman (1995) claims that cross-sectional studies can show differences and longitudinal studies can show change. How does this statement relate to the three criteria for inferring causation?

One of the most difficult components of research is to show that correlations between particular behaviors: this cannot be determined with either cross-sectional or longitudinal studies. In the case of a cross-sectional study, "Cross-sectional studies are observational in nature and are known as descriptive research, not causal or relational. Researchers record the information that is present in a population, but they do not manipulate variables. This type of research can be used to describe characteristics that exist in a population, but not to determine cause-and-effect relationships between different variables" (Cherry 2013). The members of the study are all relatively similar except for one particular variable: for example, a researcher might analyze obesity trends amongst adolescents and compare behaviors of obese vs. non-obese adolescents (the similarity in the population is age; the variable is weight).

In longitudinal studies, "researchers conduct several observations of the same subjects over a period of time, sometimes lasting many years" and thus capture data on a particular phenomenon over time (Cross-sectional vs. longitudinal studies, 2009, at Work). However, like cross-sectional studies, longitudinal studies are descriptive and do not manipulate variables. A longitudinal study might show a correlation between adolescent obesity and poverty, but there would be no way to prove that one factor caused the other because there was no way to determine time order or isolate other variables that could cause the obesity (persons who were poor might have greater genetic tendencies to obesity and the poverty might not cause the obesity). Variation might be determined if weight and changes in socioeconomic status (if a reduction in obesity was associated with improvements in income) were reflected in the study, however and offer evidence to construct a future experimental… [END OF PREVIEW]

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