Thesis (Ph. D.)--University of Wisconsin--Madison, 1974. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Thesis (LL. M.)--Judge Advocate General's School, U.S. Army, 1972. / "April 1972." Typescript. Includes bibliographical references (leaves 69-72). Also issued in microfiche.

Thesis (Ph.D.)--University of Delaware, 2007. / Principal faculty advisor: Cynthia Robbins, Dept. of Sociology & Criminal Justice. Includes bibliographical references.

Thesis (Ph. D.)--University of Iowa, 2007. / Supervisor: Daniel S. O'Leary. Includes bibliographical references (leaves [82]-94).

The passage of the 2018 Farm Bill created a legal distinction between hemp and marijuana, both of which were previously illegal under federal law. The 2018 Farm Bill federally legalized hemp which became defined as any cannabis or cannabis-derived product containing less than 0.3% Δ9-tetrahydrocannabinol (THC) by dry weight. While marijuana has a high concentration of THC, hemp has a high concentration of cannabidiol (CBD), a cannabinoid similar to THC. Aside from the concentration of specific cannabinoids, hemp and marijuana are macroscopically and microscopically indistinguishable and common forensic testing for cannabis, such as the Duquenois-Levine color test, cannot distinguish between the two. Now that the federal law has been changed, new analytical methods are needed to be able to differentiate between what is legal hemp and what is illegal marijuana. This work employs the use of two analytical methods for the differentiation of hemp and marijuana: Ultraviolet-Visible Spectroscopy (UV-Vis) and Direct Analysis in Real Time-Mass Spectrometry (DART-MS). UV-Vis would be useful for quantitating cannabinoids and is a method that is amenable to field use. Previous studies have shown that fast blue BB salt (FBBBS) complexes with THC and CBD, forming unique chromophores, which can be analyzed by UV-Vis. Seven hemp samples and five marijuana samples were analyzed using this method. The hemp samples displayed two absorbances, the first between 285–290 nanometers (nm) and the second between 469–472 nm. The marijuana samples displayed one absorbance between 292–299 nm. The preparation of the hemp samples consistently produced a light to dark orange color in the sample cuvette while the marijuana samples produced a golden yellow color. Calibration curves were prepared using THC and CBD certified reference materials in an effort to quantitate the cannabinoids in each sample. Reproducibility was an issue and r2 values varied greatly. Differences were seen within the UV-Vis spectra of each sample type but further efforts in quantitation are needed. The use of DART-MS to differentiate between hemp and marijuana is still an ongoing effort. Mass spectra were generated of the previously mentioned hemp and marijuana samples. In almost all analyses, the most abundant ion was m/z 315, the [M+H]+ ion for THC and CBD. A 359 ion was also observed within the samples, which is consistent with tetrahydrocannabinolic acid (THCA), cannabidiolic acid (CBDA) and cannabichromenic acid (CBCA). Subtle differences were seen between the two sample types although it’s difficult to determine how significant these differences are upon visual examination of the mass spectral data. Using Analyze IQ Lab chemometric software, predictive models were built using known hemp and marijuana samples. Preliminary data suggests that the methods built are successful and can correctly classify hemp and marijuana based on their mass spectral differences.

PhD, Faculty of Health Sciences, University of the Witwatersrand / Substance use is associated with mining accidents, increased health care utilisation, and economic loss. Although South Africa is a major mining country, paucity of data exists on substance use among mineworkers. To determine the prevalence of alcohol and cannabis use among mineworkers, the prevalence of accidents associated with substance use, and factors influencing substance use among this population, structured interviews of 1571 participants (involving breathalyser tests for alcohol and urine tests for cannabis), focus group discussions, and a record review of post-accident substance tests were carried out in seven mines. While structured interviews were carried out between March & October 2002, focus group discussions were carried out between May & June 2003, and record review was done between March & September 2004. Between 10.7% to 24.4% of participants across study mines, with a mean of 15.3%, are likely to be dependent on alcohol, while 4.6% to 21.5% of participants, with a mean of 9.1%, use cannabis. Between 0% and 5.9% of all breath samples, with a mean of 1.9%, contained alcohol ≥ 0.10mg/1000ml of breath, the legal limit for professional drivers. However, the majority of positive samples were collected on a Monday and day of sample collection was found to be a confounding factor. In mine P1 in 2003, 1% of samples tested in cases of accidents were positive for alcohol, and in 2002 and 2003, cannabis tests were positive in 4.9% and 3.9% of accident cases tested, respectively. v Low levels of education (p=0.020), low job categories (p=0.004) and lack of awareness of link between cannabis use and accidents (p=0.0001) were found to be positively associated with cannabis use. Being a full-time worker compared to a contract worker (p=0.004) was protective from cannabis use. While being married (p=0.001) was protective from alcohol use, there was no significant difference in the alcohol and cannabis use status of those who were married and lived with their wives at the mines and those who didn‟t live with their wives but visited them periodically. Findings of this study where alcohol use for fun (p=0.046) and relaxation (p=0.018) were associated with alcohol dependence, and where misconceptions about the energy-boosting attribute of cannabis, and perception that work is „most-times to always dangerous‟ (p=0.012) were associated with cannabis use and alcohol dependence, suggest the use of substances as a coping mechanism and highlight the link between social factors and substance use. Industry regulations employing a holistic approach and incorporating essential components, such as clear written individual mine policy, health promotion, monitoring and surveillance, Employee Assistance Programmes, disciplinary procedures and wellness programmes, can contribute towards substance use control among this population.

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Americans have long held a variety of opinions when it comes to the legalization of marijuana. While previous research has mostly focused on use rates and behavior, the purpose of this examination is to specifically analyze people's attitudes towards marijuana legalization. Of particular importance was (1) the extent to which attitudes towards marijuana legalization have changed over the past four decades and (2) how the social factors often associated with marijuana legalization attitudes have changed over the same period. Results indicate that over one-third of Americans now believe marijuana should be made legal. These pro-legalization attitudes are at their highest levels in four decades. Being younger, more educated, and liberal have been associated with these positive attitudes towards marijuana legalization. Yet age and education has become slightly less significant. Greater church attendance has remained associated with negative attitudes. While being white once correlated with anti-legalization attitudes, it is now positively associated with marijuana legalization attitudes. Finally, this study describes the remaining findings and thoughts.