Measuring disability

Housing policy researchers studying the intersection of housing and disability must understand the relative strengths and limitations of the various types of administrative and survey data that can be used to identify persons with disabilities. This article describes traditional ways that disability has been measured in U.S. Department of Housing and Urban Development (HUD) administrative data and in relevant federally funded household surveys in the United States, while also highlighting newly available linked administrative survey data that can better identify persons with disabilities who participate in HUD-assisted housing programs. The article addresses various methods of measuring disability, including measures that are common across data sources (such as the sequence of six disability questions now included in the American Community Survey, American Housing Survey, and other federally funded surveys) and measures that are unique to specific sources of data (including HUD administrative data linked with population health surveys that include more detail on activity, functional, and social limitations). The article also discusses the strengths and limitations of various measures

A Thermal Time-Constant Experiment

A simple experiment, well suited for an undergraduate course in mechatronics, is described in which thermal time-constant information is extracted from a heater-blower table-top system. In the experiment, a thermistor measures the temperature of a resistive-heater that is cooled by a blower and a microcontroller is used for data acquisition. The student is asked to determine the thermal time response, and in particular the thermal time-constant of the system, for different blower speeds. The experiment prompts questions about modeling a thermal system, and exposes the student to basic concepts of mechatronics including measurement and data analysis

Annual Compendium of Disability Statistics: 2015

Statistics are a powerful tool—in research, policymaking, program evaluation, and advocacy. They are used to frame the issues, monitor current circumstances and progress, judge the effectiveness of policies and programs, make projections about the future, and predict the costs of potential policy changes. In the United States, statistics about the population with disabilities and about the government programs that serve people with disabilities—disability statistics—are often difficult to find. Numerous government agencies generate and publish disability statistics, and as a result, disability statistics are scattered and buried in documents and websites all across the federal government. The Annual Disability Statistics Compendium is a publication of statistics about people with disabilities and about the government programs which serve them. It is modeled after the Statistical Abstracts of the United States, published yearly by the U.S. Department of Commerce. The Compendium is designed to serve as a summary of government statistics

Implementation and Perceived Effectiveness of Professional Learning Communities in the Kanawha County School District in West Virginia

The purpose of this study was to investigate teachers’ perceptions of levels of implementation and levels of effectiveness in improving student learning of Professional Learning Communities (PLCs) in Kanawha County Schools. This study also sought to determine differences in levels of implementation and effectiveness for five selected independent variables and examined the relationship between levels of implementation and levels of effectiveness. Finally, this study described teachers’ suggestions to enhance their PLC experience and identified challenges that hindered the implementation of PLCs. A researcher-developed survey was used to collect data. The study population consisted of 1,788 teachers. Respondents (N=1,017) were from 44 elementary schools, 14 middle schools, and eight high schools. Teachers reported PLC implementation levels as some of the time and most of the time and judged them to be somewhat effective and effective in improving student learning. Levels of implementation were significantly different based on organizational structure, grade/developmental level, and sex. Levels of effectiveness were significantly different based on grade/developmental level. The correlation between levels of implementation and levels of effectiveness was significant and moderately strong. Allowing schools to select content for PLC meetings and more effective team construction were the strategies most often suggested to enhance the PLC experience. The most frequently listed challenges to implementation of PLCs were negative attitude, pre-decided content and inadequate training

Snowex 2017 Community Snow Depth Measurements: A Quality-Controlled, Georeferenced Product

Snow depth was one of the core ground measurements required to validate remotely-sensed data collected during SnowEx Year 1, which occurred in Colorado. The use of a single, common protocol was fundamental to produce a community reference dataset of high quality. Most of the nearly 100 Grand Mesa and Senator Beck Basin SnowEx ground crew participants contributed to this crucial dataset during 6-25 February 2017. Snow depths were measured along ~300 m transects, whose locations were determined according to a random-stratified approach using snowfall and tree-density gradients. Two-person teams used snowmobiles, skis, or snowshoes to travel to staked transect locations and to conduct measurements. Depths were measured with a 1-cm incremented probe every 3 meters along transects. In shallow areas of Grand Mesa, depth measurements were also collected with GPS snow-depth probes (a.k.a. MagnaProbes) at ~1-m intervals. During summer 2017, all reference stake positions were surveyed with <10 cm accuracy to improve overall snow depth location accuracy. During the campaign, 193 transects were measured over three weeks at Grand Mesa and 40 were collected over two weeks in Senator Beck Basin, representing more than 27,000 depth values. Each day of the campaign depth measurements were written in waterproof field books and photographed by National Snow and Ice Data Center (NSIDC) participants. The data were later transcribed and prepared for extensive quality assessment and control. Common issues such as protocol errors (e.g., survey in reverse direction), notebook image issues (e.g., halo in the center of digitized picture), and data-entry errors (sloppy writing and transcription errors) were identified and fixed on a point-by-point basis. In addition, we strove to produce a georeferenced product of fine quality, so we calculated and interpolated coordinates for every depth measurement based on surveyed stakes and the number of measurements made per transect. The product has been submitted to NSIDC in csv format. To educate data users, we present the study design and processing steps that have improved the quality and usability of this product. Also, we will address measurement and design uncertainties, which are different in open vs. forest areas

State and Local Determinants of Employment Outcomes among Individuals with Disabilities

In the United States, employment rates among individuals with disabilities are persistently low but vary substantially. In this study, we examine the relationship between employment outcomes and features of the state and county physical, economic, and policy environment among a national sample of individuals with disabilities. To do so, we merge a set of state- and countylevel environmental variables with data from the 2009–2011 American Community Survey accessed in a U.S. Census Research Data Center. We estimate regression models of employment, work hours, and earnings as a function of health conditions, personal characteristics, and these environmental features. We find that certain environmental variables are significantly associated with employment outcomes. Although the estimated importance of environmental variables is small relative to individual health and personal characteristics, our results suggest that these variables may present barriers or facilitators to employment that can explain some geographic variation in employment outcomes across the United States

Monitoring multidimensional poverty in the U.S.

On the international stage, poverty is increasingly understood multi-dimensionally as a deprivation of wellbeing in several dimensions rather than solely as a lack of income or low consumption. In the U.S., recent research shows that many people who are not counted as poor under the official or supplemental measures of income poverty experience multidimensional poverty. Yet there is no monitoring of multidimensional poverty. This paper examines trends in multidimensional poverty in the U.S. since 2013 using a measure that includes deprivations in family income, selfreported health status, educational attainment, employment status, and health insurance coverage. Using Current Population Survey data for years 2013 to 2017, the percentage of the total population experiencing multidimensional poverty decreased significantly each year, from 13.8% in 2013 to 10.0% in 2017. However, between 2016 and 2017, the extent of the decline in multidimensional poverty was smaller than in earlier years and became less widely shared across population groups. Increased deprivations in health insurance explain this more limited decline in multidimensional poverty in 2017

Formal Network Models and Their Application to Firewall Policies (UPF-Firewall)

We present a formal model of network protocols and their application to modeling firewall policies. The formalization is based on the Unified Policy Framework (UPF). The formalization was originally developed with for generating test cases for testing the security configuration actual firewall and router (middle-boxes) using HOL-TestGen. Our work focuses on modeling application level protocols on top of tcp/ip