The core purposes of this study were twofold: (1) to ascertain whether mathematics teachers support reform oriented teaching practices, and (2) to discover whether there is correspondence between what classroom mathematics teachers say they should do when they teach mathematics and what they really do in the classroom. To carry out this investigation, elementary, middle and high school mathematics teachers responded to survey questions about their beliefs and practices and were observed. There are two major research questions that underlie this research and several secondary questions. The primary questions are: 1. Do in-service mathematics teachers support the major principles of reform oriented mathematics instruction? 2. To what extent do in-service mathematics teachers exhibit reform-oriented teaching in their classrooms? Among the secondary research questions are the following: 3. Does professional development support reform oriented teaching practices? 4. Do teachers' beliefs vary with respect to the grade level they teach? 5. Do teachers' beliefs vary with respect to their levels of education? The subjects were mathematics teachers from three grade levels, elementary, middle and high school selected from three school districts in northeastern United States. One hundred seventy-four mathematics teachers participated in the main study. Ten of the teachers who completed the Questionnaire voluntarily participated in in-class observations and post-observation interviews. The Reformed Teaching Observation Protocol (RTOP) was used for the observation. All 10 teachers were interviewed individually immediately either after the in-class observation took place or a day later. The most salient finding of the study was that while teachers express a strong belief in the major tenets of reform oriented mathematics teaching, their actual demonstration of this type of teaching is far less evident. Pearson correlation analysis demonstrated only marginal relationships between teachers' demographic characteristics and their beliefs. A multiple regression analysis found that only 6% of the variance in beliefs is accounted for by the demographic variables. One of the major conclusions of the research is that teachers feel compelled to teach in ways that are discrepant from their beliefs in order to prepare their students for the standardized tests, which are now a critical component of educational accountability. Educational implications, limitations of the study and suggestions for future research are discussed. / Educational Psychology

This qualitative, exploratory study uses an interpretive case study design to elucidate key factors influencing the attitudes and behaviors of older adults with regard to public education funding in the context of rapid demographic change. The research was conducted in three first-ring suburbs of Philadelphia, Pennsylvania, where the older population is predominately White, and students in the districts come from diverse racial backgrounds. The study examines how social networks and physical environment relate to older people’s attitudes and behaviors with respect to public education funding. Current literature about older adults in neighborhoods focuses primarily on them as recipients of service. In contrast, this study examines older people as political actors and provides a robust and nuanced discussion about how they themselves frame issues of school funding. The project makes a timely contribution to research on the relationship between the growing racial generation divide and support for public education among older adults. It also provides strategy recommendations designed to increase older people’s support for public education funding. / Urban Studies

Data Analytics (DA) has been blamed for contributing to discriminatory managerial decisions in organizations. To date, most studies have focused on the technical antecedents of such discriminations. As a result, little is known about how to ameliorate the problem by focusing on the human aspects of decision making when using DA in organizational settings. This study represents an effort to address this gap. Drawing on the cognitive elaboration model of ethical decision-making, construal level theory, and the literature on moral intensity, this study investigates how the availability and the design of demographic transparency (a form of decisional guidance) can lower DA users’ likelihood of agreement with discriminatory recommendations of DA tools. In addition, this study examines the role of user’s mindfulness and organizational ethical culture on this process. In an experimental study users interact with a DA tool that provides them with a discriminatory recommendation. The results confirm that demographic transparency significantly impacts both recognition of the moral issue at hand and perceived proximity toward the subject of the decision, which in turn help decrease the likelihood of users’ approval of the discriminatory recommendation. Moreover, the results suggest that user’s mindfulness and organizational ethical culture enhance the positive impacts of demographic transparency. / Dissertation / Doctor of Philosophy (PhD)

As a response to the increasing demand for renewable power, the solar photovoltaic (PV) market is growing fast. In addition to PV systems, the energy from solar radiation can be converted intoheat energy in solar thermal (ST) systems. This study uses a method that identifies solar energy systems using aerial imagery and deep machine learning to create and evaluate an inventory of solar energy systems in three Swedish municipalities together with socioeconomic and demographic data, to understand the relation between different variables and PV and ST adoption. The variables are age, sex, birth region, education, unemployment, average income and economic standard. Information about the locations also include owner, time at residence, tax value, purpose of property and purpose of building. The relation is analyzed through a correlation and regression analysis at three different granularity levels: households, demographic statistical areas and municipalities. Out of 692 inventoried PV systems and 399 ST systems, the majority was installed in rural or regional center areas. The most common buildings were residential and complementary. Most of the properties were owned by individuals, and the tax value of properties was in general lower for ST systems, indicating that it is more common for companies to install PV systems and at larger properties. The average income, age and percentage of males are higher for households that have adopted PV and/or ST systems compared to the municipalities average. However, the difference is clearer for PV systems than for ST systems. The analysis concludes that share of the population in age group 45-64 years, share of males, share born in Sweden and high average income have a positive correlation to PV adoption. Share of the population within age group 25-44 years, unemployment and low economic standard isfound to have a negative correlation to PV deployment. Positive correlation to ST adoption is found for a share of the population within age group 45-64 years and born in Sweden. Share of population in age group 24-44 years and unemployment was found to have a negative correlation to ST deployment.

No

The purpose of this study was to determine if significant variances exist among the attitudes of educational leaders in West Virginia toward collective bargaining and what influences certain demographic variables might have as predictors of attitudes. Eight categories of educational leaders were included in this study, with membership determined by employment or organizational position held. Twenty-one items concerning demographic information were included to gather pertinent background material. Data were collected by mail survey using a Likert Scale. The data were analyzed as follows: differences across categories of leaders were tested using the one-way analysis of variance, and predictors of attitudes were sought with a multiple regression and a Scheffe test. The results indicated that there were significant differences between groups in relation to attitudes toward collective bargaining and certain demographic variables at the .05 level of significance. / Ed. D. / incomplete_metadata

Yes / The ideology and politics of Hindu nationalism has always been predicated on an antagonistic discursive construction of ‘dangerous others,’ notably Muslims but also Christians. This construct has served to define India as first and foremost a Hindu nation, thereby de facto relegating religious minorities to the status of not properly belonging to the nation. However, under the leadership of the current Prime Minister Narendra Modi, Hindu nationalism has acquired an unprecedented political force. A key consequence of this has been that the discursive construction of dangerous others is now increasingly being written into law, through a process of Hindu nationalist statecraft. The result is, we argue, not just a de facto but increasingly also a de jure marginalization and stigmatization of religious minorities. We substantiate this argument by analysing the intent and effect of recent pieces of legislation in two Indian states regulating, among other things, religious conversions, inter-faith relationships, and population growth. Conceiving of such laws as dog-whistle legislation, we argue that they are, in fact, geared towards the legal consolidation of India as a Hindu state. We also analyse the intimate entanglement between these laws and the collective violence of vigilante groups against those minorities that Hindu nationalists frame as dangerous, anti-national others.

This research developed a system, Rx, to provide early identification and effective control of network stealth worms in digital networks through techniques based on biological epidemiology. Network stealth worms comprise a class of surreptitious, self-propagating code that spread over network connections by exploiting security vulnerabilities in hosts. Past outbreaks due to traditional worms subverted hundreds of thousands of machines. Network stealth worms exacerbate that threat by using clandestine methods to maintain a persistent presence in the network. Biological epidemiology was shown to support the real-time detection, characterization, forecasting, and containment of network stealth worms. Epidemiology describes a scientific methodology in biology that seeks to understand, explain, and control disease. Bio-mathematical modeling led to the development of a mechanism for digital networks to identify worm infection behavior buried in anomaly data, to characterize a worm, and to forecast the temporal spread of a worm. Demographic analysis of the infected hosts revealed the subset of vulnerable machines within the population. The automated response of advanced quarantine used this information to control the spread of an identified worm by isolating both infected and vulnerable machines. The novel contributions of this research included the identification of a network stealth worm at the network-level based on end-host reports while simultaneously characterizing and forecasting the spread of the worm. Additionally, this task offered the technique of advanced quarantine through demographic analysis of the population. This work resulted in a scalable, fault-tolerant strategy that dramatically enhanced the survival rate of network hosts under attack by a stealth worm. Moreover, this approach did not require new hardware, changes to existing protocols, or participation outside the implementing organization. This research showed application to a wider range of challenges. The bio-mathematical models are extensible, allowing Rx to respond to variations on the self-propagating code presented here. The approach is applicable to other forms of malware beyond self-propagating code by interchanging the epidemic model with one more appropriate. Lastly, the strategy allowed anomaly detectors to be sensitive to lower reporting thresholds and a variety of often benign yet potentially useful events. / Ph. D.

High-dose methotrexate (HD MTX) is critical for treating pediatric malignancies such as acute lymphoblastic leukemia and neuro-carcinoma. However, its significant toxicity due to drug accumulation poses substantial risks. This retrospective study assesses the impact of demographic factors on MTX toxicity and clearance in pediatric oncology patients. Patient records from Saint Mary Hospital were analyzed, focusing on two MTX administration protocols: a 24-hour infusion followed by alkaline hydration and a 4-hour infusion followed by alkaline hydration. We hypothesize that factors such as age, body surface area (BSA), and body mass index (BMI) are associated with MTX clearance and toxicity. The study found no significant difference in clearance between genders, but females exhibited higher toxicity rates. Ethnicity comparisons showed Caucasians had the fastest clearance, followed by Hispanics, African Americans, and others, with Hispanics experiencing the highest toxicity rates. Patients with a BSA of less than one had a lower risk of delayed clearance, although toxicity levels were similar across BSA groups. BMI analysis indicated that patients with a BMI over 25 were at a higher risk of toxicity. Taken together, these findings suggest the need for personalized treatment plans in pediatric oncology to enhance therapeutic efficacy and reduce adverse effects. Future research should expand the sample size and develop a risk stratification guideline to identify patients suitable for outpatient treatment.

Spatial analysis of species for which there is limited quantity of data, termed as the data-poor species, has been challenging due to limited information, especially lack of spatially explicit information. However, these species are frequently of high ecological, conservation and management interest. In this study, I used two empirical examples to demonstrate spatial analysis for two kinds of data-poor species. One example was seabird bycatch from the U.S. Atlantic pelagic longline fishery, which focused on rare events/species for which data are generally characterized by a high percentage of zero observations. The other example was endangered white abalone off the California coast, which focused on endangered species whose data are very limited. With the seabird bycatch example, I adopted a spatial filtering technique to incorporate spatial patterns and to improve model performance. The model modified with spatial filters showed superior performance over other candidate models. I also applied the geographically weighted approach to explore spatial nonstationarity in seabird bycatch, i.e., spatial variation in the parameters that describe relationships between biological processes and environmental factors. Estimates of parameters exhibited high spatial variation. With the white abalone example, I demonstrated the spatially explicit hierarchical demographic model and conducted a risk assessment to evaluate the efficacy of hypothetical restoration strategies. The model allowed for the Allee effect (i.e., density-dependent fertilization success) by using spatial explicit density estimates. Restoration efforts directed at larger-size individuals may be more effective in increasing population density than efforts focusing on juveniles. I also explored the spatial nonstationarity in white abalone catch data. I estimated the spatially explicit decline rate and linked the decline rate to environmental factors including water depth, distance to California coast, distance to land, sea surface temperature and chlorophyll concentration. The decline rate showed spatial variation. I did not detect any significant associations between decline rate and these five environmental factors. Through such a study, I am hoping to provide insights on applying or adapting existing methods to model spatial dynamics of data-poor species, and on utilizing information from such analyses to aid in their conservation and management. / Ph. D.