Farmers play a pivotal role in food production. To be economically successful, farmers must make many decisions during the course of a growing season about the allocation of inputs to production. For farmers in arid regions, one of these decisions is whether to irrigate. This research is the first of its kind to investigate the reasons that drive a farmer to make irrigation decisions and use those reasons/factors to forecast future irrigation decisions. This study can help water managers and canal operators to estimate short-term irrigation demands, thereby gaining information that might be useful in management of irrigation supply systems. This work presents three approaches to study farmer irrigation behavior: Bayesian belief networks (BBNs), decision trees, and hidden Markov models (HMMs). All three models are in the class of evolutionary algorithms, which are often used to analyze problems in dynamic and uncertain environments. These algorithms learn the connections between observed input and output data and can make predictions about future events. The models were used to study behavior of farmers in the Canal B command area, located in the Lower Sevier River Basin, Delta, Utah. Alfalfa, barley, and corn are the major crops in this area. Biophysical variables that are measured during the growing reasons were used as inputs to build the models. Information about crop phenology, soil moisture, and weather variables were compiled. Information about timing of irrigation events was available from soil moisture probes installed on some agricultural fields at the site. The models were capable of identifying the variables that are important in forecasting an irrigation decision, classes of farmers, and decisions with single and multi-factor effect regarding farmer behavior. The models did this across years and crops. The advantage of using these models to study a complex problem like behavior is that they do not require exact information, which can never be completely obtained, given the complexity of the problem. This study uses biophysical inputs to forecast decisions about water use. Such forecasts cannot be done satisfactorily using survey methodologies. The study reveals irrigation behavior characteristics. These conform to previous beliefs that a farmer might look at crop conditions, consult a neighbor, or irrigate on a weekend if he has a job during the week. When presented with new data, these models gave good estimates for probable days of irrigation, given the past behavior. All three models can be adequately used to explore farmers' irrigation behavior for a given site. They are capable of answering questions related to the driving forces of irrigation decisions and the classes of subjects involved in a complex process.

Providing consumers with usable nutrition information requires an effective labeling format. The objective of this study, which was conducted in a supermarket setting, was to determine whether consumers could, without previous instruction, make equally effective nutrition decisions using a graphic format based on nutrient density as when using the current labeling format. For comparison with other studies, a demographic, nutrition knowledge and nutrition labeling data base was collected. The questionnaire completed by each participating consumer included items regarding demographic data and shopping preferences, and questions evaluating nutrition knowledge for comparison as a data base with other studies. It also appraised the ability of the shopper to utilize two nutrition labeling formats in making nutrition decisions. Another questionnaire, completed by a researcher, assessed race, body type and build, and time taken by each participant to complete the nutrition decision questions. Six supermarkets were selected from one large Utah chain as sites for the survey. The nutrient density format produced the greatest percentage of correct responses. The difference was particularly evident when the data were analyzed for overall total correct responses. Participants who were high school graduates or had family incomes between $4,000 - $7,999 made more correct responses when utilizing the nutrient density format than when confronted with the other format. The nutrient density presentation also took less time for participants to complete. The graphical nutrient density format evaluated in the study is more effective than the current labeling format in assisting consumers to make valid nutritional decisions.

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One of the most vital decisions that teachers make during classroom discussion is whether to and how to validate the thinking that students present to the class. In this thesis I describe a study that addressed the issues that are associated with the decisions that teachers make in regards to validating students' ideas. Through qualitative research I explored these issues through videotaping an expert teacher, taking field notes, and conducting interviews. I share a description of what it looks like for one middle school mathematics teacher to make different decisions to use student input during class. The expert teacher in this study chose to use student input more than any other decision that she could have made. This study can help pre-service teachers and teachers learn to use student input.

The thesis describes a stochastic procedure developed for assessing risk and reducing uncertainty inherent in the investment decision making process. It is proposed that the two most important profitability financial ratios in relation to investment decisions are the return on equity and the return on assets respectively. In order to exploit their use as criteria for risk measurement and uncertainty reduction, a stochastic formulation is adopted in which these ratios are expressed in probabilistic terms. A density function to describe their behaviour is derived; it is found that density distribution analysis for both ratios indicate that the Weibull distribution apart from being the most flexible and adaptable model of all those considered, provides the best overall fit to the data. It is accordingly used in the latter part of the research for evaluating industrial sector and company investment risk.

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Many immigrants arrive in Canada from countries with different degrees of gender inequality. While Canada has relatively high levels of gender equality, many immigrant-origin countries are characterized by high levels of inequality between men and women. Studies show that source-country gender inequality negatively impacts immigrant women's socioeconomic outcomes in the host society. However, little is known about how source-country gender inequality impacts social aspects of immigrant adjustment in Canada. This dissertation examines how source-country gender inequality impacts acculturation, structural integration and identification. My analyses of data from the Ethnic Diversity Survey and General Social Surveys find that source-country gender inequality can benefit identification when measured by sense of belonging to Canada. In other cases, it can be a barrier when acculturation is measured by financial decision-making. Further, source-country gender inequality can have little impact on the structural integration of immigrants when measured by sport participation. The results suggest that source-country gender inequality affects immigrant men and women in complex and multifaceted ways. / Thesis / Doctor of Philosophy (PhD)

This text examines the possible impacts of prior exposure to agriculture, and how this relates to college students’ food purchasing decisions. This study will assess if college students had prior exposure to agriculture before attending college, and what type of exposure this was, as well as assess how this prior exposure may alter purchasing decisions made by students who attend Mississippi State University. To collect this data, this study used a qualitative survey method to question students enrolled in the College of Agriculture and Life Sciences at Mississippi State University and determine if there is a significant relationship between prior exposure to agriculture and the purchasing decisions of food products. It was found that a college student’s prior exposure to agriculture does in fact impact their food purchasing decisions. It is recommended that this study be replicated with a larger sample size and further research should be conducted to examine specifically how their purchasing decisions are impacted. This study could also aid in future research to find the best agriculture education methods for this specific demographic of college students ages 18-23 in order to raise agriculture literacy rates and preserve the future of the agriculture industry.

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