<p> </p> Nonpoint source (NPS) pollution refers to pollution entering receiving waterbodies from diffuse sources, and is one of the main causes of water pollution in the United States. Best management practices (BMPs) and low impact development (LID) strategies are water and land management practices geared at reducing the effect of NPS pollution. This research focused on residents in northwestern Indiana and assessed their interest in adopting BMPs and LID strategies across the urban-to-rural gradient. Resident groups of interest include medium/large-scale farmers, small-scale farmers, rural non-farming residents, suburban residents, and urban residents. Specifically, this research explored residents’ awareness of and attitudes towards water quality improvement practices, their likelihood of adopting these practices, and factors that influence their likelihood of adoption. Data was collected through a household survey that was mailed to residents of Porter and LaPorte counties. In addition to survey questions measuring respondents’ awareness, attitudes, perceptions, likelihood of adoption, and demographics, the survey also contained an experimental component in the form of an information page. By using descriptive, bivariate and multivariate statistical procedures to analyze survey data, this research found that respondents generally reported high levels of awareness of and positive attitudes towards BMPs and LID strategies. Despite this, 41% of respondents reported a likelihood of adopting any water quality improvement practices. This research found that resident groups differed in their awareness of water quality improvement practices, as well as their descriptive and subjective norms associated with adopting these practices. Respondents valued improved environmental quality and reduced flash flood risk as benefits of adopting water quality improvement practices, and identified not knowing enough about specific conservation practices and concerns about how to install and maintain the practices as main barriers to adoption. Generally, respondents who were younger, perceived more problems with various potential water pollution sources, were more aware of water quality improvement practices, had more positive attitudes, had a stronger sense of personal responsibility, sought information in the past about water quality problems, or perceived stronger social expectations from peers (i.e., subjective norms) were more likely to be interested in adopting water quality improvement practices in the next year. The role of information was more ambiguous. While information about how to choose, install and maintain specific water quality improvement practices may be useful for residents, the information treatment about the responsibility of each resident group for NPS pollution did not seem to affect respondents’ likelihood of adoption. However, this research did find that respondents reacted differently to the information provided based on their initial self-reported likelihood of adoption prior to receiving any information. Based on these results, this research suggests strategies that may be used by public and private entities to motivate residents’ adoption of water quality improvement practices, including but not limited to: (1) developing education programs that highlight both the broader environmental quality benefits and geography-specific practical benefits of water quality improvement; (2) developing technical assistance programs that help residents identify appropriate conservation practices for their homes and properties and that facilitate installation and maintenance of such practices; (3) developing communication strategies to help residents establish a sense of self-responsibility and align their perceived water quality problems with their own actions; and, (4) developing outreach programs to help establish and facilitate descriptive and subjective norms in favor of adopting water quality improvement practices at the watershed scale. <br> Nonpoint source (NPS) pollution refers to pollution entering receiving waterbodies from diffuse sources, and is one of the main causes of water pollution in the United States. Best management practices (BMPs) and low impact development (LID) strategies are water and land management practices geared at reducing the effect of NPS pollution. This research focused on residents in northwestern Indiana and assessed their interest in adopting BMPs and LID strategies across the urban-to-rural gradient. Resident groups of interest include medium/large-scale farmers, small-scale farmers, rural non-farming residents, suburban residents, and urban residents. Specifically, this research explored residents’ awareness of and attitudes towards water quality improvement practices, their likelihood of adopting these practices, and factors that influence their likelihood of adoption. Data was collected through a household survey that was mailed to residents of Porter and LaPorte counties. In addition to survey questions measuring respondents’ awareness, attitudes, perceptions, likelihood of adoption, and demographics, the survey also contained an experimental component in the form of an information page. By using descriptive, bivariate and multivariate statistical procedures to analyze survey data, this research found that respondents generally reported high levels of awareness of and positive attitudes towards BMPs and LID strategies. Despite this, 41% of respondents reported a likelihood of adopting any water quality improvement practices. This research found that resident groups differed in their awareness of water quality improvement practices, as well as their descriptive and subjective norms associated with adopting these practices. Respondents valued improved environmental quality and reduced flash flood risk as benefits of adopting water quality improvement practices, and identified not knowing enough about specific conservation practices and concerns about how to install and maintain the practices as main barriers to adoption. Generally, respondents who were younger, perceived more problems with various potential water pollution sources, were more aware of water quality improvement practices, had more positive attitudes, had a stronger sense of personal responsibility, sought information in the past about water quality problems, or perceived stronger social expectations from peers (i.e., subjective norms) were more likely to be interested in adopting water quality improvement practices in the next year. The role of information was more ambiguous. While information about how to choose, install and maintain specific water quality improvement practices may be useful for residents, the information treatment about the responsibility of each resident group for NPS pollution did not seem to affect respondents’ likelihood of adoption. However, this research did find that respondents reacted differently to the information provided based on their initial self-reported likelihood of adoption prior to receiving any information. Based on these results, this research suggests strategies that may be used by public and private entities to motivate residents’ adoption of water quality improvement practices, including but not limited to: (1) developing education programs that highlight both the broader environmental quality benefits and geography-specific practical benefits of water quality improvement; (2) developing technical assistance programs that help residents identify appropriate conservation practices for their homes and properties and that facilitate installation and maintenance of such practices; (3) developing communication strategies to help residents establish a sense of self-responsibility and align their perceived water quality problems with their own actions; and, (4) developing outreach programs to help establish and facilitate descriptive and subjective norms in favor of adopting water quality improvement practices at the watershed scale.

O objetivo deste trabalho é o desenvolvimento de uma ferramenta de simulação baseada em multiagentes para calcular a emergência de parcerias entre múltiplos agentes. A metodologia adotada foi tomar como base o sistema PART-NET [CONTE’98], que efetua o cálculo da emergência de parcerias entre uma dupla de agentes, e alterá-lo de acordo com o objetivo proposto. Dessa maneira, dividiu-se o trabalho em duas etapas. Na primeira, o sistema original foi reescrito na linguagem Java, promovendo benefícios operacionais, como a melhora da interface e a apresentação dos resultados de forma gráfica. Esse sistema intermediário foi denominado PartNET+. A segunda etapa constituiu-se em expandir a funcionalidade do sistema intermediário, tornando sua arquitetura de agentes mais completa pela adição de planos, o que permite novos tipos de parcerias. Para processar essas parcerias, criou-se um novo algoritmo para cálculo de parcerias entre múltiplos agentes, com base em hipergrafos. O sistema resultante, que compreende estas extensões funcionais, foi denominado PartNET++. / The purpose of this work is the development of a multiagent based simulation tool to account partnership formation among multiple agents. In order to achieve that, the PART-NET [CONTE’98] system was adopted as a base. This system calculates the partnership formation of pairs of agents, and was altered according to the proposed objective. In this manner, the work was divided in two stages. In the first, the original system was redesigned using the Java language, bringing operational improvements to the predecessor, such as user interface enhancement and graphical display of the results. This intermediary system was named PartNET+. The second stage promotes new functionality to this intermediary system, adding plans to its agent architecture to allow new kinds of partnerships. A new algorithm for multiple agents partnership formation was developed based on hipergraphs, and the final system that handles this enhanced partnership formation was called PartNET++

Social psychology has a long tradition of studying the personality traits associated with subjective well-being (SWB). However, research often depends on a priori but unempirical assumptions about how to (a) measure the constructs, and (b) mitigate confounded associations. These assumptions have caused profligate and often contradictory findings. To remedy, I demonstrate how a computational psychology paradigm-predicated on large online data and iterative analyses-might help isolate more robust personality trait associations. At the outset, I focussed on univariate measurement. In the first set of studies, I evaluated the extent researchers could measure psychological characteristics at scale from online behaviour. Specifically, I used a combination of simulated and real-world data to determine whether predicted constructs like big five personality were accurate for specific individuals. I found that it was usually more effective to simply assume everyone was average for the characteristic, and that imprecision was not remedied by collapsing predicted scores into buckets (e.g. low, medium, high). Overall, I concluded that predictions were unlikely to yield precise individual-level insights, but could still be used to examine normative group-based tendencies. In the second set of studies, I evaluated the construct validity of a novel SWB scale. Specifically, I repurposed the balanced measure of psychological needs (BMPN), which was originally designed to capture the substrates of intrinsic motivation. I found that the BMPN robustly captured (a) dissociable experiences of suffering and flourishing, (b) more transitive SWB than the existing criterion measure, and (c) unique variation in real-world outcomes. Thus, I used it as my primary outcome. Then, I focussed on bivariate associations. The third set of studies extracted pairs of participants with similar patterns of covarying personality traits-and differing target traits-to isolate less-confounded SWB correlations. I found my extraction method-an adapted version of propensity score matching-outperformed even advanced machine learning alternatives. The final set of studies isolated the subset of facets that had the most robust associations with SWB. It combined real-world surveys with a total of eight billion simulated participants to find the traits most prevalent in extreme suffering and flourishing. For validation purposes, I first found that depression and cheerfulness-the trait components of SWB-were highly implicated in both suffering and flourishing. Then, I found that self-discipline was the only other trait implicated in both forms of SWB. However, there were also domain-specific effects: anxiety, vulnerability and cooperation were implicated in just suffering; and, assertiveness, altruism and self-efficacy were implicated in just flourishing. These seven traits were most likely to be the definitive, stable, drivers of SWB because their effects were totally consistent across the full range of intrapersonal contexts.

O objetivo deste trabalho é o desenvolvimento de uma ferramenta de simulação baseada em multiagentes para calcular a emergência de parcerias entre múltiplos agentes. A metodologia adotada foi tomar como base o sistema PART-NET [CONTE’98], que efetua o cálculo da emergência de parcerias entre uma dupla de agentes, e alterá-lo de acordo com o objetivo proposto. Dessa maneira, dividiu-se o trabalho em duas etapas. Na primeira, o sistema original foi reescrito na linguagem Java, promovendo benefícios operacionais, como a melhora da interface e a apresentação dos resultados de forma gráfica. Esse sistema intermediário foi denominado PartNET+. A segunda etapa constituiu-se em expandir a funcionalidade do sistema intermediário, tornando sua arquitetura de agentes mais completa pela adição de planos, o que permite novos tipos de parcerias. Para processar essas parcerias, criou-se um novo algoritmo para cálculo de parcerias entre múltiplos agentes, com base em hipergrafos. O sistema resultante, que compreende estas extensões funcionais, foi denominado PartNET++. / The purpose of this work is the development of a multiagent based simulation tool to account partnership formation among multiple agents. In order to achieve that, the PART-NET [CONTE’98] system was adopted as a base. This system calculates the partnership formation of pairs of agents, and was altered according to the proposed objective. In this manner, the work was divided in two stages. In the first, the original system was redesigned using the Java language, bringing operational improvements to the predecessor, such as user interface enhancement and graphical display of the results. This intermediary system was named PartNET+. The second stage promotes new functionality to this intermediary system, adding plans to its agent architecture to allow new kinds of partnerships. A new algorithm for multiple agents partnership formation was developed based on hipergraphs, and the final system that handles this enhanced partnership formation was called PartNET++

Thesis (M. Sc. (Statistics) / Most social and health science data are longitudinal and additionally multilevel in nature, which means that response data are grouped by attributes of some cluster. Ignoring the differences and similarities generated by these clusters results to misleading estimates, hence motivating for a need to assess variance components (VCs) using multilevel models (MLMs) or generalised linear mixed models (GLMMs). This study has explored and fitted teenage pregnancy census data that were gathered from 2011 to 2015 by the Africa Centre at Kwa-Zulu Natal, South Africa. The exploration of these data revealed a two level pure hierarchy data structure of teenage pregnancy status for some years nested within female teenagers. To fit these data, the effects that census year (year) and three female characteristics (namely age (age), number of household membership (idhhms), number of children before observation year (nch) have on teenage pregnancy were examined. Model building of this work, firstly, fitted a logit gen eralised linear model (GLM) under the assumption that teenage pregnancy measurements are independent between females and secondly, fitted a GLMM or MLM of female random effect. A better fit GLMM indicated, for an additional year on year, a 0.203 decrease on the log odds of teenage pregnancy while GLM suggested a 0.21 decrease and 0.557 increase for each additional year on age and year, respectively. A GLM with only year effect uncovered a fixed estimate which is higher, by 0.04, than that of a better fit GLMM. The inconsistency in the effect of year was caused by a significant female cluster variance of approximately 0.35 that was used to compute the VCs. Given the effect of year, the VCs suggested that 9.5% of the differences in teenage pregnancy lies between females while 0.095 similarities (scale from 0 to 1) are for the same female. It was also revealed that year does not vary within females. Apart from the small differences between observed estimates of the fitted GLM and GLMM, this work produced evidence that accounting for cluster effect improves accuracy of estimates. Keywords: Multilevel Model, Generalised Linear Mixed Model, Variance Components, Hier archical Data Structure, Social Science Data, Teenage Pregnancy

Dynamics between student teacher ethnicity and the practices of culturally plural curricula seeks to improve student performance and strives to minimize the achievement gap. This quantitative study explored whether there was a significant difference in the North Carolina Final Exam history-social science test performance between (a) African American and Hispanic students taught by a teacher from a different ethnic makeup and (b) African American and Hispanic students taught by a teacher from a similar ethnic makeup in 8th grade of social science classes. Student's performance is a key factor in evaluating the credibility of a school which is crucial to all stakeholders. The theoretical framework for this study centered around Tillmans' theory of culturally sensitive education which focused on variations of academic achievement based on student's engagements with teachers who share their cultural background or teachers who teach curricula that reflects their own cultures. Data were collected from a purposeful sampling of depersonalized archival records of 2,000 8th grade African American and Hispanic students who took the North Carolina Final Exam for Social Sciences. Data were analyzed using causal-comparative approach and focused on the fixed factor of race with 3 covariates and teacher race as the dependent variable. Results indicated that there was a significant difference in the students performance depending on the ethnicity of their teacher. Students with a teacher of their ethnic background, performed better compared to having a teacher from a different ethnic background. This study contributes to social change through the understanding of how teacher diversity and the need for relational teaching can promote greater academic achievement within their classrooms.

De nombreux domaines ont intérêt à étudier les points de vue exprimés en ligne, que ce soit à des fins de marketing, de cybersécurité ou de recherche avec l'essor des humanités numériques. Nous proposons dans ce manuscrit deux contributions au domaine de la fouille de points de vue, axées sur la difficulté à obtenir des données annotées de qualité sur les médias sociaux. Notre première contribution est un jeu de données volumineux et complexe de 22853 profils Twitter actifs durant la campagne présidentielle française de 2017. C'est l'un des rares jeux de données considérant plus de deux points de vue et, à notre connaissance, le premier avec un grand nombre de profils et le premier proposant des communautés politiques recouvrantes. Ce jeu de données peut être utilisé tel quel pour étudier les mécanismes de campagne sur Twitter ou pour évaluer des modèles de détection de points de vue ou des outils d'analyse de réseaux. Nous proposons ensuite deux modèles génériques semi-supervisés de détection de points de vue, utilisant une poignée de profils-graines, pour lesquels nous connaissons le point de vue, afin de catégoriser le reste des profils en exploitant différentes proximités inter-profils. En effet, les modèles actuels sont généralement fondés sur les spécificités de certaines plateformes sociales, ce qui ne permet pas l'intégration de la multitude de signaux disponibles. En construisant des proximités à partir de différents types d'éléments disponibles sur les médias sociaux, nous pouvons détecter des profils suffisamment proches pour supposer qu'ils partagent une position similaire sur un sujet donné, quelle que soit la plateforme. Notre premier modèle est un modèle ensembliste séquentiel propageant les points de vue grâce à un graphe multicouche représentant les proximités entre les profils. En utilisant des jeux de données provenant de deux plateformes, nous montrons qu'en combinant plusieurs types de proximité, nous pouvons correctement étiqueter 98% des profils. Notre deuxième modèle nous permet d'observer l'évolution des points de vue des profils pendant un événement, avec seulement un profil-graine par point de vue. Ce modèle confirme qu'une grande majorité de profils ne changent pas de position sur les médias sociaux, ou n'expriment pas leur revirement. / Numerous domains have interests in studying the viewpoints expressed online, be it for marketing, cybersecurity, or research purposes with the rise of computational social sciences. We propose in this manuscript two contributions to the field of stance detection, focused around the difficulty of obtaining annotated data of quality on social medias. Our first contribution is a large and complex dataset of 22853 Twitter profiles active during the French presidential campaign of 2017. This is one of the rare datasets that considers a non-binary stance classification and, to our knowledge, the first one with a large number of profiles, and the first one proposing overlapping political communities. This dataset can be used as-is to study the campaign mechanisms on Twitter, or used to test stance detection models or network analysis tools. We then propose two semi-supervised generic stance detection models using a handful of seed profiles for which we know the stance to classify the rest of the profiles by exploiting various proximities. Indeed, current stance detection models are usually grounded on the specificities of some social platforms, which is unfortunate since it does not allow the integration of the multitude of available signals. By infering proximities from differents types of elements available on social medias, we can detect profiles close enough to assume they share a similar stance on a given subject. Our first model is a sequential ensemble algorithm which propagates stances thanks to a multi-layer graph representing proximities between profiles. Using datasets from two platforms, we show that, by combining several types of proximities, we can achieve excellent results. Our second model allows us to observe the evolution of profiles' stances during an event with as little as one seed profile by stance. This model confirms that a large majority of profiles do not change their stance on social medias, or do not express their change of heart.

This qualitative study describes maternal and paternal experiences of thirty-five Samoans living in Auckland, Aotearoa New Zealand. The study was conducted in order to establish, "What, if any changes to parenting practices have occurred since their family migrated into New Zealand?Through interviews, respondents discussed their values, attitudes and beliefs and how they perceived that they were brought up by their own parents. They also described and discussed their own roles as parents and the roles of their children. They also discussed how the church influenced the ways in which their parents parented them and the way they themselves parent their children. Respondents were chosen via a snowball technique of referrals from four different church ministers. The four churches were selected on the recommendation of one Samoan Church Minister as being representative of the Samoan community. Four ministers were interviewed, along with four elders and five parents from each church. Seven other people from outside these churches, four not church attenders were also interviewed in order to be able to further explore the importance and effects of the churches. The theoretical approach engaged a combination of the principles of Grounded Theory (Glaser & Strauss, 1967) and the 'Fa'afaletui,' (Tamasese, 1997.) The latter is a Samoan framework which gives a multi-layered approach to data interpretation using a range of lenses and perspectives. In conducting this investigation, the combination of Western and Samoan frameworks was appropriate especially given the cultural sensitivities that were apparent around the topic matter and the ethnicity of the respondents and the researcher. Earlier findings, concerning discipline by (Fairbairn-Dunlop, 2002) were affirmed, as were findings about fa'alavelave from the earlier study into parenting practices (McCallum et al, 2000). In this present study, it was found that enculturation (i.e changes in culture) over time, modified parenting practices and specifically that inter-generational perspectives about parenting practices were apparent. Evidence of conflicting approaches to values between generations was encountered and a range of rituals were adapted as a consequence of migration and time; discipline and fa'alavelave were prime examples of this. The relative paucity of a body of Pasifika literature and Pacific research by Pacific people, from which a theoretical foundation for a study of this kind could be developed, was seen to be problematic. It is concluded that enculturation following migration spawns a reconstruction of values and associated practices in parenting and that previously held core values concerning discipline, the church and the family become altered over time and generations. It is also suggested that future research should seek to corroborate the findings of this study by examining the parenting practices of the next generation.

This study examines the readability of text books used by Year 11 students at a Secondary College in the A.C.T. Twenty-seven texts are examined with the majority being taken from the area of Social Science. The texts are examined using the following measures, The Fry Readability Index, The SMOG Formula, The Cloze Measure, The number of Words per T-Unit and the level of Abstraction of the text. According to these indices between 60% and 84% of the texts are too difficult for students commencing Year 11. This study also examined the interrelationship between the indices. A feature of this study is that it introduces into readability measures a consideration of the number of words per T-Unit and level of Abstraction

<p>Att uppnå en hög lönsamhet och produktivitet är viktiga prioriteringar inom organisationer. Mycket pekar på att ett effektivt arbetsmiljöarbete ökar dem båda. Det finns indikationer på att arbetsmiljöarbete inte utnyttjas för att ge lönsamhet. Till synes verkar inte den kunskapen vara allmänt känd. I arbetsmiljöarbete finns pedagogiska processer, då främst i den psykosociala arbetsmiljön. Ett perspektiv inom arbetslivspedagogiken är att vidareutbildning och kunskapsutveckling har som yttersta syfte att öka organisationens produktivitet. Syftet med litteraturstudien har varit att dels få fram hur lönsamhet definieras i ett urval texter, dels att få veta på vilket sätt arbetsmiljöarbete kan påverka lönsamhet. För att besvara frågeställningarna begränsades urvalet till att endast inkludera texter innehållande arbetsmiljöarbete, någon form av lönsamhet samt effekter av det. Sexton texter inkluderades i urvalet, till dem användes en textanalysmall som bestod av fyra frågor. Oavsett hur de olika texterna definierar lönsamhet gör resultatet tydligt att arbetsmiljöarbete på många sätt är ekonomiskt lönsamt. Svaren anger att stora delar av vad som påverkar lönsamheten är psykosociala faktorer. Två slutsatser, som båda påvisas av 50 % av de utvalda texterna, är att lönsamhet uppnås genom att förbättra de anställdas hälsa samt att ledarskapet har stor betydelse för en organisations lönsamhet.</p>