Social Disorganization and Sex Offenders in Minneapolis, MN: A Socio-Spatial Analysis

Using a combination of techniques stemming from the spatial analysis approach of Geography, structural-functionalist theory in Sociology, and an ecological perspective of Criminology, this thesis addresses where sex offenders reside and why. Analyses were performed using the twin cities of Minneapolis and St. Paul, Minnesota as a typical urban setting. The study fuses multiple disciplines work on the complex social problem of released risk level III sex offender management in a spatially-conscious, micro-scale analysis attempting to understand the distribution of released offenders and the relevance of social disorganization theory in explaining their distribution. Socio-economic status and family disruption are tested and found to be important components of a generalized or fuzzy correlation between calculated social disorganization and offender settlement. In concert with other recent research in the U.S., residential stability is a variable of limited determinate capability. In an attempt to understand the fuzzy correlation, this fused analysis develops urban design considerations for mitigation of offender concentrations as well as other insights for policy and management. Inclusive in this analysis is the revelation that offenders often settle in physically and socially disrupted `wedge,\u27 or isolated neighborhoods. It suggests the merit of complimentary quantitative and qualitative analysis techniques in urban socio-spatial analysis

Error in Demographic and Other Quantitative Data and Analyses

This paper is about errors in statistical data. My remarks are in two parts. The first part deals with the proposition that the statistical data we consume, analyse and produce contain more error from more sources than we sometimes recognise. The second asks: How can we better deal with these errors? The topic of error in statistics can become highly technical, but for the most part this is not a technical presentation. It deals with common sense and experience; much of it is anecdotal

Potential mechanisms underlying the decision to use a seat belt: a literature review

The purpose of this literature review was to serve as the background knowledgebase for a 5-year cooperative agreement between NHTSA and the University of Michigan. This discretionary cooperative agreement is intended to study promising lines of research that elucidate the mechanisms that underlie risk perception and can be applied to converting part-time belt users to full-time users. The overall goal of this cooperative agreement is to develop testable strategies, based on basic and applied research, for influencing risk perception to move motor vehicle occupants from part-time to full-time use of seat belts. Specific topics covered in this literature review are: individual belt user characteristics; social influences on belt use; applications from research on other risky behaviors; policy/enforcement/incentive; communication and education; and technology. Conclusions are drawn within each section and for the review overall.National Highway Traffic Safety Administrationhttp://deepblue.lib.umich.edu/bitstream/2027.42/110521/1/103147.pdfDescription of 103147.pdf : final repor

Middle School Student Records as Dropout Indicators

Dropping out of school is associated with a wide array of negative outcomes and the extraordinarily high United States dropout rate has brought the issue to the forefront of American education. This study investigated normally collected middle school data from a suburban Colorado school district to determine the predictive value toward students dropping out or graduating from high school. Accessed was a longitudinal data set of first year in middle school records, 7th grade, from 1999-2003 for students that graduated or dropped out from a Colorado suburban high school from 2003-2007. Discriminate function analysis was utilized on 2,195 student school records, that included 106 dropout and 2,089 graduate student academic and demographic data, to determine the strength of the data to predict group membership. Middle school student\u27s metamorphosis from child to adolescent is a uniquely critical time in a student\u27s growth due to physical, social, psychological, and brain synaptic pruning. Dropping out of school is influenced by a wide array of external and internal school concerns but if clear set of red flags were available for easy identification of at risk students concerned school personal may best bring interventions to bear in the middle school setting. This study found that for this data set there was a slight correlation between grades in Language Arts and Math with a greater predictive power from Social Studies, Science, and Physical Education, subjects often overlooked in other studies. The conclusion stated that a clear set of warning signals was found with a strong enough probability of dropout identification to be considered as warning indicators and therefore all indicators need to be considered for every child on an individual level

Predictive Modelling of Retail Banking Transactions for Credit Scoring, Cross-Selling and Payment Pattern Discovery

Evaluating transactional payment behaviour offers a competitive advantage in the modern payment ecosystem, not only for confirming the presence of good credit applicants or unlocking the cross-selling potential between the respective product and service portfolios of financial institutions, but also to rule out bad credit applicants precisely in transactional payments streams. In a diagnostic test for analysing the payment behaviour, I have used a hybrid approach comprising a combination of supervised and unsupervised learning algorithms to discover behavioural patterns. Supervised learning algorithms can compute a range of credit scores and cross-sell candidates, although the applied methods only discover limited behavioural patterns across the payment streams. Moreover, the performance of the applied supervised learning algorithms varies across the different data models and their optimisation is inversely related to the pre-processed dataset. Subsequently, the research experiments conducted suggest that the Two-Class Decision Forest is an effective algorithm to determine both the cross-sell candidates and creditworthiness of their customers. In addition, a deep-learning model using neural network has been considered with a meaningful interpretation of future payment behaviour through categorised payment transactions, in particular by providing additional deep insights through graph-based visualisations. However, the research shows that unsupervised learning algorithms play a central role in evaluating the transactional payment behaviour of customers to discover associations using market basket analysis based on previous payment transactions, finding the frequent transactions categories, and developing interesting rules when each transaction category is performed on the same payment stream. Current research also reveals that the transactional payment behaviour analysis is multifaceted in the financial industry for assessing the diagnostic ability of promotion candidates and classifying bad credit applicants from among the entire customer base. The developed predictive models can also be commonly used to estimate the credit risk of any credit applicant based on his/her transactional payment behaviour profile, combined with deep insights from the categorised payment transactions analysis. The research study provides a full review of the performance characteristic results from different developed data models. Thus, the demonstrated data science approach is a possible proof of how machine learning models can be turned into cost-sensitive data models

The role of women in disputing among the Ila of Zambia: political adaptation in legal change

African Studies Center Working Paper No. 46This article examines the role of female litigants within the changing social context of disputing and dispute processing among the Ila of Zambia. While the historical and contemporary case material upon which this article is based ultimately reveals a complexity of substantive and procedural points of law across the spectrum of disputing modes and disputing forums available to aggrieved Ila females, here I am more concerned with the elaboration of social realities in legal process -- the social forces which shape legal expectations. Such elaboration, I argue, requires not only an examination of law and dispute settlement, but also the political context of disputing and dispute processing. This article, therefore, addresses itself to rather skeletal theory generated from research conducted under the broad heading of "the politics of law." [TRUNCATED

State Public-Law Litigation in an Age of Polarization

Public-law litigation by state governments plays an increasingly prominent role in American governance. Although public lawsuits by state governments designed to challenge the validity or shape the content of national policy are not new, such suits have increased in number and salience over the last few decades — especially since the tobacco litigation of the late 1990s. Under the Obama and Trump Administrations, such suits have taken on a particularly partisan cast; “red” states have challenged the Affordable Care Act and President Obama’s immigration orders, for example, and “blue” states have challenged President Trump’s travel bans and attempts to roll back prior environmental policies. As a result, longstanding concerns about state litigation as a form of national policymaking that circumvents ordinary lawmaking processes have been joined by new concerns that state litigation reflects and aggravates partisan polarization. This Article explores the relationship between state litigation and the polarization of American politics. As we explain, our federal system can mitigate the effects of partisan polarization by taking some divisive issues off the national agenda, leaving them to be solved in state jurisdictions where consensus may be more attainable — both because polarization appears to be dampened at the state level, and because political preferences are unevenly distributed geographically. State litigation can both help and hinder this dynamic. The available evidence suggests that state attorneys general (who handle the lion’s share of state litigation) are themselves fairly polarized, as are certain categories of state litigation. We map out the different ways states can use litigation to shape national policy, linking each to concerns about polarization. We thus distinguish between “vertical” conflicts, in which states sue to preserve their autonomy to go their own way on divisive issues, and “horizontal” conflicts, in which different groups of states vie for control of national policy. The latter, we think, will tend to aggravate polarization. But we concede — and illustrate — that it will often be difficult to separate out the vertical and horizontal aspects of particular disputes, and that in some horizontal disputes the polarization costs of state litigation may be worth paying. We argue, moreover, that state litigation cannot be understood in a vacuum, but must be assessed as part of a broader phenomenon in American law: our reliance on entrepreneurial litigation to develop and enforce public norms. In this context, state attorneys general often play roles similar to “private attorneys general” such as class action lawyers or public interest organizations. And states, with their built-in systems of democratic accountability and internal checks and balances, compare well with other entrepreneurial enforcement vehicles in a number of respects. Nevertheless, state litigation efforts may not always account well for divergent preferences and interests within the broad publics that the states represent, and this deficiency becomes particularly important in politically polarized times. Although our account of state litigation is, on the whole, a positive one, we caution that state attorneys general face a significant risk of backlash by other political actors, and by courts, if state litigation is (or is perceived to be) a bitterly partisan affair

"I Should Be Pregnant So Many Times By Now": Risk Perception, Numeracy, and Young Women's Contraceptive Use

Conception is probabilistic: any instance of sexual intercourse without contraception may lead to a pregnancy, but whether any one instance of sex results in pregnancy is a matter of chance. The underlying probability of conceiving is not easily inferred from either outcome, and judgments about risk require fairly sophisticated quantitative reasoning skills (numeracy) that many Americans adults do not have. Still, women’s deliberations about risk may be tremendously important for their subsequent behavior. In this dissertation, I consider the impact of risk perception and health numeracy on young women’s contraceptive use. I use data from the Relationship Dynamics & Social Life study, a longitudinal survey of women aged 18/19 living in a Michigan county. RDSL data include weekly measurement of sex, contraception, pregnancy desire, and pregnancies, and quarterly measurement of women’s estimates of their pregnancy risk. The first empirical chapter finds evidence of a reciprocal relationship between women’s pregnancy risk estimates and their actual experiences with sex, contraception, and pregnancy. I find that women’s pregnancy risk estimates tend to decrease over time. Women who avoid pregnancy despite having sex without contraception tend to revise their estimates of pregnancy risk downward; in turn, lower estimates of pregnancy risk predict sex without contraception in later weeks. The second empirical chapter examines a competing set of risk perceptions: women’s concerns about side effects and other long-term health consequences of hormonal contraception. Sex without contraception is more likely and more frequent among women expressing greater concerns about side effects. Side effect concerns predict less use of the contraceptive pill/patch/ring, intrauterine devices (IUDs), and contraceptive implants, and more reliance on non-hormonal methods such as condoms and withdrawal. The final empirical chapter considers whether low numeracy is related to ineffective contraceptive use. In this analysis, I categorize women as low, medium, or high numeracy based on the logical consistency of their answers to survey items about the risk of pregnancy. Numeracy is not associated with women’s sexual behavior, but it does predict contraceptive use among sexually active women. Lower numeracy is associated with a higher likelihood and higher frequency of sex without contraception, more gaps in contraceptive use, and more switches to less effective contraceptive methods. Lower numeracy women also have lower odds of using the pill/patch/ring, IUD, and implant versus condoms as their primary method of contraception. Collectively, these analyses demonstrate that misunderstandings about the risk and probabilistic nature of pregnancy, concerns about contraceptive side effects, and poor numeracy are barriers to effective contraceptive use among young women who wish to avoid or delay pregnancy.PHDSociologyUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/143977/1/ejela_1.pd