Managing Risk in a Culture of Rights: Providing Support and Treatment in Community-Based Settings for Persons with Intellectual Disabilities who Sexually Offend

People with intellectual disability who sexually offend commonly live in community-based settings since the closing of all institutions across the province of Ontario. Nine (n=9) front line staff who provide support to these individuals in three different settings (treatment setting, transitional setting, residential setting) were interviewed. Participants responded to 47 questions to explore how sex offenders with intellectual disability can be supported in the community to prevent re-offenses. Questions encompassed variables that included staff attitudes, various factors impacting support, structural components of the setting, quality of life and the good life, staff training, staff perspectives on treatment, and understanding of risk management. Three overlapping models that have been supported in the literature were used collectively for the basis of this research: The Good Lives Model (Ward & Gannon, 2006; Ward et al., 2007), the quality of life model (Felce & Perry, 1995), and variables associated with risk management. Results of this research showed how this population is being supported in the community with an emphasis on the following elements: positive and objective staff attitude, teamwork, clear rules and protocols, ongoing supervision, consistency, highly trained staff, and environments that promote quality of life. New concepts arose which suggested that all settings display an unequal balance of upholding human rights and managing risks when supporting this high-risk population. This highlights the need for comprehensive assessments in order to match the offender to the proper setting and supports, using an integration of a Risk, Need, Responsivity model and the Good Lives model for offender rehabilitation and to reduce the likelihood of re-offenses.

A case study of the Ottawa Valley whitewater rafting industry : standards and risks

This qualitative case study identifies and discusses the standards and risk management practices of the Ottawa Valley whitewater rafting industry and the impacts of the government enforced Special-purpose Vessels Regulations are discussed. Data collection occurred using a single case study design, which included interviews and document analysis. This study found that internal, industry, and actual standards are influenced through a variety of sources. These standards were found to affect the risk management practices of commercial whitewater rafting providers. In general, these standards promoted a high level of risk management within the Ottawa Valley rafting industry. The Special-purpose Vessels Regulations were found to be non-influential in raising the risk management standards of the Ottawa Valley whitewater rafting industry.

The information content of Canadian implied volatility indexes

For predicting future volatility, empirical studies find mixed results regarding two issues: (1) whether model free implied volatility has more information content than Black-Scholes model-based implied volatility; (2) whether implied volatility outperforms historical volatilities. In this thesis, we address these two issues using the Canadian financial data. First, we examine the information content and forecasting power between VIXC - a model free implied volatility, and MVX - a model-based implied volatility. The GARCH in-sample test indicates that VIXC subsumes all information that is reflected in MVX. The out-of-sample examination indicates that VIXC is superior to MVX for predicting the next 1-, 5-, 10-, and 22-trading days' realized volatility. Second, we investigate the predictive power between VIXC and alternative volatility forecasts derived from historical index prices. We find that for time horizons lesser than 10-trading days, VIXC provides more accurate forecasts. However, for longer time horizons, the historical volatilities, particularly the random walk, provide better forecasts. We conclude that VIXC cannot incorporate all information contained in historical index prices for predicting future volatility.