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• 1. [Article] Intimate Partner Violence During the Transition from Prison to the Community: An Ecological Analysis

  While extensive research has been conducted on the causes of intimate partner violence in the community, very little is known about rates and predictors of domestic violence perpetrated by offenders who ...

  Citation × Citation Citation Abstract Copy Title: Intimate Partner Violence During the Transition from Prison to the Community: An Ecological Analysis Author: Freeland Braun, Margaret Joy Year: 2012 While extensive research has been conducted on the causes of intimate partner violence in the community, very little is known about rates and predictors of domestic violence perpetrated by offenders who have recently been incarcerated. Some evidence suggests that formerly incarcerated individuals may be at an increased risk to perpetrate intimate partner violence during the transition from prison to the community (e.g., Hairston & Oliver 2006; Hilton, Harris, Popham, & Lang, 2010; Oliver & Hairston, 2008). The primary goal of this dissertation was to examine the extent to which former inmates engage in domestic violence during the transition from prison to the community. A second goal of this dissertation was to determine the independent and interactive effects of selected individual, situational, and social-structural factors on post-prison domestic violence. The current dissertation project involved a retrospective study of data collected from n = 1,137 formerly-incarcerated male offenders who were released from state prison between 2004 and 2009. Data regarding individual-level factors of borderline and antisocial personality characteristics and exposure to family-of-origin violence were extracted from institutional records. Additional individual-level demographic characteristics including offenders' age, ethnicity, education need, marital status, number of children, crime of conviction, length of incarceration, and participation in correctional rehabilitation programs extracted from institutional records were also considered. The situational-level factor of offenders' employment after prison release was also collected from institutional records; and the social-structural factor of neighborhood disadvantage was collected from information available in offenders' community supervision records and Census tract-level data. The outcome measure of post-prison domestic violence was gathered from local law enforcement records. Data were entered into statistical models to predict post-prison domestic violence. Main effects on post-prison domestic violence were examined for each of the individual-level demographic characteristics, borderline and antisocial personality features, exposure to family-of-origin violence, employment, and neighborhood disadvantage. Interactive effects on post-prison domestic violence were examined between borderline and antisocial personality characteristics, exposure to family-of-origin violence, employment, and neighborhood disadvantage. Significant predicted main effects on post-prison domestic violence included age, ethnicity, education need, number of children, violent criminal history, attendance of substance abuse treatment in prison, witnessing interparental violence as a child, and neighborhood disadvantage. Significant predicted interaction effects on post-prison domestic violence included the interaction between physical abuse as a child and neighborhood disadvantage. Implications for policies regarding post-prison supervision sentencing, housing, and the advancement of programming to prevent intimate partner violence during the transition from prison to the community are discussed. Contributions to the literature on intimate partner violence, environmental transition theory, and ecological theoretical frameworks are also addressed. Title: Intimate Partner Violence During the Transition from Prison to the Community: An Ecological Analysis Author: Freeland Braun, Margaret Joy Year: 2012 While extensive research has been conducted on the causes of intimate partner violence in the community, very little is known about rates and predictors of domestic violence perpetrated by offenders who have recently been incarcerated. Some evidence suggests that formerly incarcerated individuals may be at an increased risk to perpetrate intimate partner violence during the transition from prison to the community (e.g., Hairston & Oliver 2006; Hilton, Harris, Popham, & Lang, 2010; Oliver & Hairston, 2008). The primary goal of this dissertation was to examine the extent to which former inmates engage in domestic violence during the transition from prison to the community. A second goal of this dissertation was to determine the independent and interactive effects of selected individual, situational, and social-structural factors on post-prison domestic violence. The current dissertation project involved a retrospective study of data collected from n = 1,137 formerly-incarcerated male offenders who were released from state prison between 2004 and 2009. Data regarding individual-level factors of borderline and antisocial personality characteristics and exposure to family-of-origin violence were extracted from institutional records. Additional individual-level demographic characteristics including offenders' age, ethnicity, education need, marital status, number of children, crime of conviction, length of incarceration, and participation in correctional rehabilitation programs extracted from institutional records were also considered. The situational-level factor of offenders' employment after prison release was also collected from institutional records; and the social-structural factor of neighborhood disadvantage was collected from information available in offenders' community supervision records and Census tract-level data. The outcome measure of post-prison domestic violence was gathered from local law enforcement records. Data were entered into statistical models to predict post-prison domestic violence. Main effects on post-prison domestic violence were examined for each of the individual-level demographic characteristics, borderline and antisocial personality features, exposure to family-of-origin violence, employment, and neighborhood disadvantage. Interactive effects on post-prison domestic violence were examined between borderline and antisocial personality characteristics, exposure to family-of-origin violence, employment, and neighborhood disadvantage. Significant predicted main effects on post-prison domestic violence included age, ethnicity, education need, number of children, violent criminal history, attendance of substance abuse treatment in prison, witnessing interparental violence as a child, and neighborhood disadvantage. Significant predicted interaction effects on post-prison domestic violence included the interaction between physical abuse as a child and neighborhood disadvantage. Implications for policies regarding post-prison supervision sentencing, housing, and the advancement of programming to prevent intimate partner violence during the transition from prison to the community are discussed. Contributions to the literature on intimate partner violence, environmental transition theory, and ecological theoretical frameworks are also addressed. Close

• 2. [Article] Development of an operational system for monitoring the changes in urban subarea residential housing status: a spatial analytic application of the formulations of neighborhood filtering and neighborhood dynamics

  This dissertation focuses on the precise and meaningful measurement of change as it pertains to the urban subarea residential housing status. The word "measurement" is qualified as meaningful in the sense ...

  Citation × Citation Citation Abstract Copy Title: Development of an operational system for monitoring the changes in urban subarea residential housing status: a spatial analytic application of the formulations of neighborhood filtering and neighborhood dynamics Author: Mba, Harold Chike Year: 1982 This dissertation focuses on the precise and meaningful measurement of change as it pertains to the urban subarea residential housing status. The word "measurement" is qualified as meaningful in the sense that the approach adopted is of relevance to public policy. Specifically, the dissertation is aimed at providing answers to the following research questions: First, how can the changes in residential housing status in the different parts of an urban area be precisely and meaningfully measured? Second, what variables are most appropriate for the measurement? Third, can these variables be useful for differentiating between various parts of the urban area? Fourth, do the resul ts of an urban subarea housing classification system depend on the specific variables used in the classification? Using data drawn mainly from the 1960 and 1970 censuses of housing for Portland, Oregon SMSA, a simple but robust methodology is developed for indexing and monitoring changes in the urban subarea residential housing status. The research borrows appreciably from Fisher and Winnick's, and Toulan' s formulations of the filtering process in the urban housing market. The variables used in the measurement and classification analyses include the changes in the following variables: median home value or contract rent, median household income relative to the average household size, housing quality, percentage of all occupied housing units, and percentage of owner occupied housing units. Principal component analysis is used for construction of composite index of change in urban subarea residential housing status. Furthermore, this composite index is used in a multivariate linear discriminant analysis for the classification of the various subareas (census tracts) in Portland, Oregon SMSA. The findings validate the variables employed in the analyses, and support the hypothesis that the results of an urban subarea classification system depend, to some extent, on the housing market variables used in the classification. The findings from the study show that operationally simple but robust systems can be developed for monitoring the changes in residential housing status in urban neighborhoods, in relation to the general urban area. Title: Development of an operational system for monitoring the changes in urban subarea residential housing status: a spatial analytic application of the formulations of neighborhood filtering and neighborhood dynamics Author: Mba, Harold Chike Year: 1982 This dissertation focuses on the precise and meaningful measurement of change as it pertains to the urban subarea residential housing status. The word "measurement" is qualified as meaningful in the sense that the approach adopted is of relevance to public policy. Specifically, the dissertation is aimed at providing answers to the following research questions: First, how can the changes in residential housing status in the different parts of an urban area be precisely and meaningfully measured? Second, what variables are most appropriate for the measurement? Third, can these variables be useful for differentiating between various parts of the urban area? Fourth, do the resul ts of an urban subarea housing classification system depend on the specific variables used in the classification? Using data drawn mainly from the 1960 and 1970 censuses of housing for Portland, Oregon SMSA, a simple but robust methodology is developed for indexing and monitoring changes in the urban subarea residential housing status. The research borrows appreciably from Fisher and Winnick's, and Toulan' s formulations of the filtering process in the urban housing market. The variables used in the measurement and classification analyses include the changes in the following variables: median home value or contract rent, median household income relative to the average household size, housing quality, percentage of all occupied housing units, and percentage of owner occupied housing units. Principal component analysis is used for construction of composite index of change in urban subarea residential housing status. Furthermore, this composite index is used in a multivariate linear discriminant analysis for the classification of the various subareas (census tracts) in Portland, Oregon SMSA. The findings validate the variables employed in the analyses, and support the hypothesis that the results of an urban subarea classification system depend, to some extent, on the housing market variables used in the classification. The findings from the study show that operationally simple but robust systems can be developed for monitoring the changes in residential housing status in urban neighborhoods, in relation to the general urban area. Close

• 3. [Article] On the Estimation of Volumes of Roadways: An Investigation of Stop-Controlled Minor Legs

  This effort seeks to answer the question; can a transferable model be developed from easily obtainable, publicly available land-use, census, roadway, and network data for the use in safety performance ...

  Citation × Citation Citation Abstract Copy Title: On the Estimation of Volumes of Roadways: An Investigation of Stop-Controlled Minor Legs Author: Barnett, Joel Stephen Year: 2015 This effort seeks to answer the question; can a transferable model be developed from easily obtainable, publicly available land-use, census, roadway, and network data for the use in safety performance functions? 474 stop-controlled minor legs were used as the training data set using ordinary least squares regression. A best-fit model of maximum independent variables, n=12 was chosen using an exhaustive approach using Mallow's Cp to select the model with least bias in the predictors. The results of the analysis revealed that the combination of variables from Washington, Ohio, and North Carolina did not have a strong relationship. The best-fit model incorporated functional class information of the major-leg, minor leg functional class information, longitudinal markings, access to a parking lot, and population density of census tract. Validation of the model demonstrated an average 59 percent error between the model estimated and actual AADT values for validation data set (n=54). Furthermore, separate models for each state revealed a lack of uniformity in the dependent variables, and more variance description of the state specific AADT. Title: On the Estimation of Volumes of Roadways: An Investigation of Stop-Controlled Minor Legs Author: Barnett, Joel Stephen Year: 2015 This effort seeks to answer the question; can a transferable model be developed from easily obtainable, publicly available land-use, census, roadway, and network data for the use in safety performance functions? 474 stop-controlled minor legs were used as the training data set using ordinary least squares regression. A best-fit model of maximum independent variables, n=12 was chosen using an exhaustive approach using Mallow's Cp to select the model with least bias in the predictors. The results of the analysis revealed that the combination of variables from Washington, Ohio, and North Carolina did not have a strong relationship. The best-fit model incorporated functional class information of the major-leg, minor leg functional class information, longitudinal markings, access to a parking lot, and population density of census tract. Validation of the model demonstrated an average 59 percent error between the model estimated and actual AADT values for validation data set (n=54). Furthermore, separate models for each state revealed a lack of uniformity in the dependent variables, and more variance description of the state specific AADT. Close

• 4. [Article] Assessing Environmental Inequality in Portland, Oregon: An Exploration of Local Environmental Justice Struggles

  This thesis explores patterns of environmental inequality in Portland, Oregon; both the existence of spatial environmental inequalities and the structural and local forces which contribute to them. Research ...

  Citation × Citation Citation Abstract Copy Title: Assessing Environmental Inequality in Portland, Oregon: An Exploration of Local Environmental Justice Struggles Author: Folks, Jordan Douglas Year: 2012 This thesis explores patterns of environmental inequality in Portland, Oregon; both the existence of spatial environmental inequalities and the structural and local forces which contribute to them. Research on environmental inequality, or inequitable exposure to toxins, has shown that minority and low-income populations experience the bulk of the exposure to environmental hazards. Although Portland is often cited as the archetype of a sustainable city, environmental inequality is a pervasive issue. This thesis examines the health inequalities that characterize underserved communities in Portland. Utilizing a mixed methods approach, the researcher uses 1) logistic regression to statistically assess the relationship between race, poverty, and Superfund site locations, and 2) in-depth interviews with members of Oregon's environmental justice movement to help understand the historical, social, political, and economic conditions of Portland and their subsequent influence on environmental inequalities. Quantitative data is pooled from 2000 census and 2011 Environmental Protection Agency (EPA) sources. The quantitative findings demonstrate that environmental inequality is present in Portland, with African Americans being particularly overrepresented in tracts with Superfund sites. The quantitative analyses ultimately suggest that minimally populated, highly impoverished tracts with approximately 11% African American residents are most likely to house a Superfund site. The qualitative findings show that a variety of structural and local forces play prominent roles in the formation of Portland's environmental inequalities. The qualitative analyses reveal this to be a multifaceted and complex process that is indicative of Portland's history of racial inequality, contemporary free market and business forces, and governmental interests which culminate in trends of inequitable development. Title: Assessing Environmental Inequality in Portland, Oregon: An Exploration of Local Environmental Justice Struggles Author: Folks, Jordan Douglas Year: 2012 This thesis explores patterns of environmental inequality in Portland, Oregon; both the existence of spatial environmental inequalities and the structural and local forces which contribute to them. Research on environmental inequality, or inequitable exposure to toxins, has shown that minority and low-income populations experience the bulk of the exposure to environmental hazards. Although Portland is often cited as the archetype of a sustainable city, environmental inequality is a pervasive issue. This thesis examines the health inequalities that characterize underserved communities in Portland. Utilizing a mixed methods approach, the researcher uses 1) logistic regression to statistically assess the relationship between race, poverty, and Superfund site locations, and 2) in-depth interviews with members of Oregon's environmental justice movement to help understand the historical, social, political, and economic conditions of Portland and their subsequent influence on environmental inequalities. Quantitative data is pooled from 2000 census and 2011 Environmental Protection Agency (EPA) sources. The quantitative findings demonstrate that environmental inequality is present in Portland, with African Americans being particularly overrepresented in tracts with Superfund sites. The quantitative analyses ultimately suggest that minimally populated, highly impoverished tracts with approximately 11% African American residents are most likely to house a Superfund site. The qualitative findings show that a variety of structural and local forces play prominent roles in the formation of Portland's environmental inequalities. The qualitative analyses reveal this to be a multifaceted and complex process that is indicative of Portland's history of racial inequality, contemporary free market and business forces, and governmental interests which culminate in trends of inequitable development. Close

• 5. [Article] What Do We Know About Location Affordability in U.S. Shrinking Cities?

  In late 2013, the Department of Housing and Urban Development (HUD) launched the Location Affordability Index (LAI) portal. Their dataset uses models to estimate typical amount households spend on housing ...

  Citation × Citation Citation Abstract Copy Title: What Do We Know About Location Affordability in U.S. Shrinking Cities? Author: Ganning, Joanna, Tighe, Jenna Rosie Year: 2017 In late 2013, the Department of Housing and Urban Development (HUD) launched the Location Affordability Index (LAI) portal. Their dataset uses models to estimate typical amount households spend on housing and transportation at the block group level, and calculates “H + T Affordability,” the percent of household income spent on these items. In our previous research, we analyzed 81 shrinking cities to determine how location affordability differs across various neighborhoods. Our results suggest that households in declining neighborhoods, as compared to stable or redeveloping neighborhoods, face the greatest H + T affordability challenges in shrinking cities. Furthermore, in declining neighborhoods, virtually all of the additional affordability challenges encountered can be accounted for by differences in transportation affordability rather than housing. Since there is virtually no research to either validate or suggest bias in the LAI data, and a declining neighborhood in a shrinking city presents both a relatively common yet entirely dissimilar context to the norm, we feel that this data should be carefully calibrated to, and tested for, this setting to ensure that appropriate and efficient policy follow. In this report, we present the results of two research phases: a strictly quantitative first stage in which the LAI is disassembled and reassembled, taking stock of assumptions, methods, and accuracy. This work finds that the LAI generally over-estimates housing costs, but more for renters and more in metropolitan areas. Estimations of transportation cost burdens are built largely from unreliable data and using models which cannot be replicated, leading us to conclude that these cost burden estimates may not be reliable. In the second research phase, which is survey-based, we gather household-level data from 12 Census tracts in Cleveland, Ohio, to estimate household housing and transportation costs and cost burdens and gain a clearer sense of budget trade-offs where costs are unaffordable. The survey results support the first research stage. The LAI over-estimates housing costs for these neighborhoods by approximately 17% and transportation costs by approximately 126%, meaning the LAI estimates for transportation are not reliable. By and large, households trade essentials, investing, and paying bills (at all or in full) to cover their costs in housing and transportation. Title: What Do We Know About Location Affordability in U.S. Shrinking Cities? Author: Ganning, Joanna, Tighe, Jenna Rosie Year: 2017 In late 2013, the Department of Housing and Urban Development (HUD) launched the Location Affordability Index (LAI) portal. Their dataset uses models to estimate typical amount households spend on housing and transportation at the block group level, and calculates “H + T Affordability,” the percent of household income spent on these items. In our previous research, we analyzed 81 shrinking cities to determine how location affordability differs across various neighborhoods. Our results suggest that households in declining neighborhoods, as compared to stable or redeveloping neighborhoods, face the greatest H + T affordability challenges in shrinking cities. Furthermore, in declining neighborhoods, virtually all of the additional affordability challenges encountered can be accounted for by differences in transportation affordability rather than housing. Since there is virtually no research to either validate or suggest bias in the LAI data, and a declining neighborhood in a shrinking city presents both a relatively common yet entirely dissimilar context to the norm, we feel that this data should be carefully calibrated to, and tested for, this setting to ensure that appropriate and efficient policy follow. In this report, we present the results of two research phases: a strictly quantitative first stage in which the LAI is disassembled and reassembled, taking stock of assumptions, methods, and accuracy. This work finds that the LAI generally over-estimates housing costs, but more for renters and more in metropolitan areas. Estimations of transportation cost burdens are built largely from unreliable data and using models which cannot be replicated, leading us to conclude that these cost burden estimates may not be reliable. In the second research phase, which is survey-based, we gather household-level data from 12 Census tracts in Cleveland, Ohio, to estimate household housing and transportation costs and cost burdens and gain a clearer sense of budget trade-offs where costs are unaffordable. The survey results support the first research stage. The LAI over-estimates housing costs for these neighborhoods by approximately 17% and transportation costs by approximately 126%, meaning the LAI estimates for transportation are not reliable. By and large, households trade essentials, investing, and paying bills (at all or in full) to cover their costs in housing and transportation. Close

• 6. [Article] Determinants of Single Family Residential Water Use Across Scales in Four Western US Cities

  A growing body of literature examines urban water sustainability with increasing evidence that locally-based physical and social spatial interactions contribute to water use. These studies however are ...

  Citation × Citation Citation Abstract Copy Title: Determinants of Single Family Residential Water Use Across Scales in Four Western US Cities Author: Chang, Heejun, Bonnette, Matthew Ryan, Stoker, Philip, Crow-Miller, Britt, Wentz, Elizabeth A, Year: 2017 A growing body of literature examines urban water sustainability with increasing evidence that locally-based physical and social spatial interactions contribute to water use. These studies however are based on single-city analysis and often fail to consider whether these interactions occur more generally. We examine a multi-city comparison using a common set of spatially-explicit water, socioeconomic, and biophysical data. We investigate the relative importance of variables for explaining the variations of single family residential (SFR) water uses at Census Block Group (CBG) and Census Tract (CT) scales in four representative western US cities - Austin, Phoenix, Portland, and Salt Lake City, - which cover a wide range of climate and development density. We used both ordinary least squares regression and spatial error regression models to identify the influence of spatial dependence on water use patterns. Our results show that older downtown areas show lower water use than newer suburban areas in all four cities. Tax assessed value and building age are the main determinants of SFR water use across the four cities regardless of the scale. Impervious surface area becomes an important variable for summer water use in all cities, and it is important in all seasons for arid environments such as Phoenix. CT level analysis shows better model predictability than CBG analysis. In all cities, seasons, and spatial scales, spatial error regression models better explain the variations of SFR water use. Such a spatially-varying relationship of urban water consumption provides additional evidence for the need to integrate urban land use planning and municipal water planning. (C) 2017 Elsevier B.V. All rights reserved. Title: Determinants of Single Family Residential Water Use Across Scales in Four Western US Cities Author: Chang, Heejun, Bonnette, Matthew Ryan, Stoker, Philip, Crow-Miller, Britt, Wentz, Elizabeth A, Year: 2017 A growing body of literature examines urban water sustainability with increasing evidence that locally-based physical and social spatial interactions contribute to water use. These studies however are based on single-city analysis and often fail to consider whether these interactions occur more generally. We examine a multi-city comparison using a common set of spatially-explicit water, socioeconomic, and biophysical data. We investigate the relative importance of variables for explaining the variations of single family residential (SFR) water uses at Census Block Group (CBG) and Census Tract (CT) scales in four representative western US cities - Austin, Phoenix, Portland, and Salt Lake City, - which cover a wide range of climate and development density. We used both ordinary least squares regression and spatial error regression models to identify the influence of spatial dependence on water use patterns. Our results show that older downtown areas show lower water use than newer suburban areas in all four cities. Tax assessed value and building age are the main determinants of SFR water use across the four cities regardless of the scale. Impervious surface area becomes an important variable for summer water use in all cities, and it is important in all seasons for arid environments such as Phoenix. CT level analysis shows better model predictability than CBG analysis. In all cities, seasons, and spatial scales, spatial error regression models better explain the variations of SFR water use. Such a spatially-varying relationship of urban water consumption provides additional evidence for the need to integrate urban land use planning and municipal water planning. (C) 2017 Elsevier B.V. All rights reserved. Close

• 7. [Article] Wider Dissemination of Household Travel Survey Data Using Geographical Perturbation Methods

  Public agencies spend vast amounts of money collecting information about passenger travel in household travel surveys. These data are valuable for the rich and detailed information they provide, which ...

  Citation × Citation Citation Abstract Copy Title: Wider Dissemination of Household Travel Survey Data Using Geographical Perturbation Methods Author: Clifton, Kelly J., Gehrke, Steven R. Year: 2014 Public agencies spend vast amounts of money collecting information about passenger travel in household travel surveys. These data are valuable for the rich and detailed information they provide, which contribute to regional and statewide travel demand models. These data have utility beyond travel demand modeling in their application to transportation policy and travel behavior research. As the demand on these data increase, so have the quantity of information collected. Detailed geospatial referencing of the home, work and other travel destinations are common practice and permit the integration with other spatially archived data sources, such as land use characteristics, transportation system information, and other built environment, social and economic data. Other public agencies, private consultancies, non-profits and educational institutions may benefit from access to the original data with applications to areas such public health, equity, transportation safety and urban planning. Oregon Modeling Collaborative (OMC) has entered into an agreement with Oregon Modeling Steering Committee (OMSC) to host and make available Oregon Household Activity Survey (OHAS) datasets. But wide distribution of these important and expensive data is limited by the requirement to protect the confidentiality of survey participants, who are guaranteed anonymity in exchange for participation. Data are often aggregated to a geographic level such as Census tracts or transportation analysis zones (TAZs) before disseminating to the public, which limits the utility of this information. This project aims to develop a methodology to permit dissemination of these spatially-explicit data to a wider range of public constituents while at the same time, protecting the identities of study participants. Making use of these data, this project will use geographical perturbation methods to add noise to the original data to protect confidentiality while at the same time allowing the detailed geo-spatial referencing to be included in the disseminated data. The process includes: The coordinates (locations) will be geographically perturbed (masked) so that they do not reveal the identity of the traveler while at the same time retaining spatial relevance and resolution. Here the limits of the perturbation (minimum and maximum displacement) need to be determined that a) ensure confidentiality and b) minimize the errors introduced to the data. The original and perturbed (masked) data will be compared using various statistical approaches to develop a set of confidence measures for different types of transportation applications. For example, geographically perturbed (masked) may be more robust for automobile travel measures, such as vehicle miles traveled (VMT) or transit accessibility than for detailed pedestrian or bicycle trip attributes. This exercise will allow spatially-explicit OHAS data to be released to the public with some information about the confidence to which it can be applied. These data will be archived at Portland State University and made available to the public. The information and algorithms can be shared with other agencies collecting and archiving travel data, such as the National Household Travel Survey, metropolitan planning organizations and state departments of transportation, to permit wider dissemination of their data. Title: Wider Dissemination of Household Travel Survey Data Using Geographical Perturbation Methods Author: Clifton, Kelly J., Gehrke, Steven R. Year: 2014 Public agencies spend vast amounts of money collecting information about passenger travel in household travel surveys. These data are valuable for the rich and detailed information they provide, which contribute to regional and statewide travel demand models. These data have utility beyond travel demand modeling in their application to transportation policy and travel behavior research. As the demand on these data increase, so have the quantity of information collected. Detailed geospatial referencing of the home, work and other travel destinations are common practice and permit the integration with other spatially archived data sources, such as land use characteristics, transportation system information, and other built environment, social and economic data. Other public agencies, private consultancies, non-profits and educational institutions may benefit from access to the original data with applications to areas such public health, equity, transportation safety and urban planning. Oregon Modeling Collaborative (OMC) has entered into an agreement with Oregon Modeling Steering Committee (OMSC) to host and make available Oregon Household Activity Survey (OHAS) datasets. But wide distribution of these important and expensive data is limited by the requirement to protect the confidentiality of survey participants, who are guaranteed anonymity in exchange for participation. Data are often aggregated to a geographic level such as Census tracts or transportation analysis zones (TAZs) before disseminating to the public, which limits the utility of this information. This project aims to develop a methodology to permit dissemination of these spatially-explicit data to a wider range of public constituents while at the same time, protecting the identities of study participants. Making use of these data, this project will use geographical perturbation methods to add noise to the original data to protect confidentiality while at the same time allowing the detailed geo-spatial referencing to be included in the disseminated data. The process includes: The coordinates (locations) will be geographically perturbed (masked) so that they do not reveal the identity of the traveler while at the same time retaining spatial relevance and resolution. Here the limits of the perturbation (minimum and maximum displacement) need to be determined that a) ensure confidentiality and b) minimize the errors introduced to the data. The original and perturbed (masked) data will be compared using various statistical approaches to develop a set of confidence measures for different types of transportation applications. For example, geographically perturbed (masked) may be more robust for automobile travel measures, such as vehicle miles traveled (VMT) or transit accessibility than for detailed pedestrian or bicycle trip attributes. This exercise will allow spatially-explicit OHAS data to be released to the public with some information about the confidence to which it can be applied. These data will be archived at Portland State University and made available to the public. The information and algorithms can be shared with other agencies collecting and archiving travel data, such as the National Household Travel Survey, metropolitan planning organizations and state departments of transportation, to permit wider dissemination of their data. Close

• 8. [Article] Determinants of the variations in the presence of the subfamily in U.S. metropolitan areas, 1980

  Over the years there has been interest in the living arrangements of Americans and the factors which influence those arrangements. Researchers have considered the growth of families headed by women, household ...

  Citation × Citation Citation Abstract Copy Title: Determinants of the variations in the presence of the subfamily in U.S. metropolitan areas, 1980 Author: Umude, John Ossaiedeme Year: 1986 Over the years there has been interest in the living arrangements of Americans and the factors which influence those arrangements. Researchers have considered the growth of families headed by women, household consisting of single individuals, and those composed of unrelated individuals. One area, however, on which little attention has been focused is the presence of extended family living, characterized by the subfamily. The aim of this dissertation is to establish if subfamilies are a random or systematic phenomenon, and to identify the factors responsible for the variations in its occurrences within and across U.S. metropolitan areas. A causal model which accounts for the systematic variations in the presence of the subfamily was developed and tested on the metropolitan and census tract levels. The technique of path analysis was employed and analysis was performed on two geographical levels (SMSA and census tract) using the 1980 census data to ascertain if conclusions were consistent at different levels of data aggregation. The variables employed in the analysis were grouped in four major categories--demographic, sociocultural, economic and housing characteristics. A major finding of this study is that the subfamily is systematically predicted by demographic, sociocultural and economic characteristics and not by the housing variables. It suggests that subfamily will exist regardless of the housing conditions. There were some differences and similarities in the results of the two geographical levels, but overall, the findings indicate that variations of subfamilies is consistent between the two aggregate levels. The model developed held fairly well as predicted except for the housing variables. The research findings suggest that subfamily may be both a voluntary and involuntary phenomenon. Given this, a number of questions were raised that must be addressed in determining whether subfamily living is a symptom of a major social problem or if it is an acceptable alternative family structure for some families in contemporary society. It might even represent both possibilities simultaneously. These questions cannot be addressed with the type of data used in this study. Future research should be directed toward addressing them. If subfamily living is determined to be a problem, future research should help planners and policy makers formulate and implement programs that will alleviate the negative consequences of subfamily life. Title: Determinants of the variations in the presence of the subfamily in U.S. metropolitan areas, 1980 Author: Umude, John Ossaiedeme Year: 1986 Over the years there has been interest in the living arrangements of Americans and the factors which influence those arrangements. Researchers have considered the growth of families headed by women, household consisting of single individuals, and those composed of unrelated individuals. One area, however, on which little attention has been focused is the presence of extended family living, characterized by the subfamily. The aim of this dissertation is to establish if subfamilies are a random or systematic phenomenon, and to identify the factors responsible for the variations in its occurrences within and across U.S. metropolitan areas. A causal model which accounts for the systematic variations in the presence of the subfamily was developed and tested on the metropolitan and census tract levels. The technique of path analysis was employed and analysis was performed on two geographical levels (SMSA and census tract) using the 1980 census data to ascertain if conclusions were consistent at different levels of data aggregation. The variables employed in the analysis were grouped in four major categories--demographic, sociocultural, economic and housing characteristics. A major finding of this study is that the subfamily is systematically predicted by demographic, sociocultural and economic characteristics and not by the housing variables. It suggests that subfamily will exist regardless of the housing conditions. There were some differences and similarities in the results of the two geographical levels, but overall, the findings indicate that variations of subfamilies is consistent between the two aggregate levels. The model developed held fairly well as predicted except for the housing variables. The research findings suggest that subfamily may be both a voluntary and involuntary phenomenon. Given this, a number of questions were raised that must be addressed in determining whether subfamily living is a symptom of a major social problem or if it is an acceptable alternative family structure for some families in contemporary society. It might even represent both possibilities simultaneously. These questions cannot be addressed with the type of data used in this study. Future research should be directed toward addressing them. If subfamily living is determined to be a problem, future research should help planners and policy makers formulate and implement programs that will alleviate the negative consequences of subfamily life. Close

• 9. [Article] Understanding Travel Modes to Non-work Destinations: Analysis of an Establishment Survey in Portland, Oregon

  During the past three decades, research in travel behavior has generally proceeded from broad-level, aggregate analysis of mode share--the proportions of walking, bicycling, transit, and vehicle travel ...

  Citation × Citation Citation Abstract Copy Title: Understanding Travel Modes to Non-work Destinations: Analysis of an Establishment Survey in Portland, Oregon Author: Muhs, Christopher D. Year: 2013 During the past three decades, research in travel behavior has generally proceeded from broad-level, aggregate analysis of mode share--the proportions of walking, bicycling, transit, and vehicle travel occurring in traffic analysis zones, census tracts, neighborhood, or other geographical units--to fine-grained, disaggregate analysis of mode choices and other trip-making attributes at the individual level. One potential issue is whether there are differences in the types of conclusions drawn from results of analyses performed at these different levels, as these results directly inform transportation planning and policy. This thesis aims in part to confirm whether the types of conclusions drawn from different levels of analysis are different, and to what extent. We also examine the relationships between the built environment and non-work travel choices from a unique analysis perspective. To do this, we use data from a 2011 travel intercept survey in the Portland, Oregon metropolitan region that was administered at convenience store, bar, and restaurant establishments. We estimate, for each of the travel modes--walk, bicycle, and automobile--two analysis models: one binary logistic regression model for mode choice of the individual traveler going to the establishment and one multiple linear regression model for mode share of shoppers at the establishment. Both models control for socio-demographics, trip characteristics, and built environment measures of travelers. For the binary logistic regression models, the data are disaggregate and particular to the individual traveler. These models also controlled for attitudes and preference towards travel modes. For the multiple regression models, data are aggregated to the establishment. The built environment data in each model represent characteristics of urban form surrounding the establishment. The data being oriented to the destination-end of the trip, as well as providing controls on land use make this analysis unique in the literature, as most non-work travel studies use residential-based data. Results suggest that analyses performed at the two different levels provide policy-relevant but somewhat different conclusions. In general, characteristics of the individual and the trip have stronger associations with mode choices of individuals than when aggregated to the establishment and analyzed against the mode share patterns of shoppers. Instead, mode shares have stronger relationships with characteristics of the built environment. The built environment surrounding the destination has a much more pronounced association with mode shares at the establishment than with mode choices of individuals. The results highlight the usefulness of simple aggregate analysis, when appropriate. We also find large differences between modes in which characteristics are important for mode choice and mode share. Walking and automobile models behave somewhat similarly but in opposite directions, while bicycling behaves quite differently. These differences suggest on their own a move away from non-motorized travel to be considered as equivalent or assessed as one item in research and in practice. Title: Understanding Travel Modes to Non-work Destinations: Analysis of an Establishment Survey in Portland, Oregon Author: Muhs, Christopher D. Year: 2013 During the past three decades, research in travel behavior has generally proceeded from broad-level, aggregate analysis of mode share--the proportions of walking, bicycling, transit, and vehicle travel occurring in traffic analysis zones, census tracts, neighborhood, or other geographical units--to fine-grained, disaggregate analysis of mode choices and other trip-making attributes at the individual level. One potential issue is whether there are differences in the types of conclusions drawn from results of analyses performed at these different levels, as these results directly inform transportation planning and policy. This thesis aims in part to confirm whether the types of conclusions drawn from different levels of analysis are different, and to what extent. We also examine the relationships between the built environment and non-work travel choices from a unique analysis perspective. To do this, we use data from a 2011 travel intercept survey in the Portland, Oregon metropolitan region that was administered at convenience store, bar, and restaurant establishments. We estimate, for each of the travel modes--walk, bicycle, and automobile--two analysis models: one binary logistic regression model for mode choice of the individual traveler going to the establishment and one multiple linear regression model for mode share of shoppers at the establishment. Both models control for socio-demographics, trip characteristics, and built environment measures of travelers. For the binary logistic regression models, the data are disaggregate and particular to the individual traveler. These models also controlled for attitudes and preference towards travel modes. For the multiple regression models, data are aggregated to the establishment. The built environment data in each model represent characteristics of urban form surrounding the establishment. The data being oriented to the destination-end of the trip, as well as providing controls on land use make this analysis unique in the literature, as most non-work travel studies use residential-based data. Results suggest that analyses performed at the two different levels provide policy-relevant but somewhat different conclusions. In general, characteristics of the individual and the trip have stronger associations with mode choices of individuals than when aggregated to the establishment and analyzed against the mode share patterns of shoppers. Instead, mode shares have stronger relationships with characteristics of the built environment. The built environment surrounding the destination has a much more pronounced association with mode shares at the establishment than with mode choices of individuals. The results highlight the usefulness of simple aggregate analysis, when appropriate. We also find large differences between modes in which characteristics are important for mode choice and mode share. Walking and automobile models behave somewhat similarly but in opposite directions, while bicycling behaves quite differently. These differences suggest on their own a move away from non-motorized travel to be considered as equivalent or assessed as one item in research and in practice. Close

• 10. [Article] An Examination of Gentrification and Related Displacement of Black Residents in Portland's Boise Neighborhood, 1990-2010

  Issues related to gentrification and its primary consequence, the displacement of vulnerable populations from their homes and communities, are rightly considered among the most pressing social concerns ...

  Citation × Citation Citation Abstract Copy Title: An Examination of Gentrification and Related Displacement of Black Residents in Portland's Boise Neighborhood, 1990-2010 Author: Jordan, Jordan Year: 2013 Issues related to gentrification and its primary consequence, the displacement of vulnerable populations from their homes and communities, are rightly considered among the most pressing social concerns faced by urban communities. Portland, Oregon has seen many of its neighborhoods undergo the gentrification transition, especially in traditionally Black neighborhoods. The Boise neighborhood lies within Northeast Portland's Albina district, which has served as the cultural and commercial heart of Portland's Black community for generations. In the 1990 Census, over 70% of the population of Boise (situated within Multnomah County Census tract 34.02) were Black, while 26% were White. By 2010, those figures had shifted to 25% Black and 65% White. During this same period public and private investment in the neighborhood increased substantially, while indicators of gentrification such as median household income, per capita income, housing values and rents, and educational attainment showed significant corresponding increases. Through comparative analyses of Census and American Community Survey data (using 1990, 2000, and 2010 Census data for tract 34.02, as well as intervening ACS 3-year estimates), documentary review, and interviews with longtime residents and community stakeholders, this study explores the process of gentrification in the Boise neighborhood and illustrates the extent of resulting displacement of Black residents from the area. Title: An Examination of Gentrification and Related Displacement of Black Residents in Portland's Boise Neighborhood, 1990-2010 Author: Jordan, Jordan Year: 2013 Issues related to gentrification and its primary consequence, the displacement of vulnerable populations from their homes and communities, are rightly considered among the most pressing social concerns faced by urban communities. Portland, Oregon has seen many of its neighborhoods undergo the gentrification transition, especially in traditionally Black neighborhoods. The Boise neighborhood lies within Northeast Portland's Albina district, which has served as the cultural and commercial heart of Portland's Black community for generations. In the 1990 Census, over 70% of the population of Boise (situated within Multnomah County Census tract 34.02) were Black, while 26% were White. By 2010, those figures had shifted to 25% Black and 65% White. During this same period public and private investment in the neighborhood increased substantially, while indicators of gentrification such as median household income, per capita income, housing values and rents, and educational attainment showed significant corresponding increases. Through comparative analyses of Census and American Community Survey data (using 1990, 2000, and 2010 Census data for tract 34.02, as well as intervening ACS 3-year estimates), documentary review, and interviews with longtime residents and community stakeholders, this study explores the process of gentrification in the Boise neighborhood and illustrates the extent of resulting displacement of Black residents from the area. Close