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This project interrogates the United States' national fixation on the answer to the question: Who are you? In this article, it is posed that identity documentation practices arising out of the Chinese Exclusion Act era cast identity as an empirical and immutable phenomenon, specifically in response to the racialization of American-born Chinese settlers as duplicitous, through the mechanisms that information is collected, the actual information itself, and the cross-references or connections created between cases. Through tracing this lineage, racialized identification data is identified and theorized as part of hegemonic data regimes. [ABSTRACT FROM AUTHOR]

Chinese students studying abroad have been increasing rapidly in the past decades and become a significant financial contribution to receiving countries. Accordingly, understanding their enrollment choice is essential to facilitate college marketing and admission strategies. Though the decision process is believed to be different from domestic students, empirical analysis of Chinese students' enrollment choices is still lacking. This paper fills the void by examining the influential factors of Chinese students' enrollment choice with novel student-level data. We find that in addition to factors domestic students typically consider, such as financial aid and academic quality, Chinese students particularly emphasize college ranking, reputation, and location in their decision process. Furthermore, unlike domestic students who usually prefer colleges with proximity to home, Chinese students' location preference is linked to job prosperity. We also find that the impact of the factors varies for students from different regions of China, which can be attributable to uneven economic development within the country.

Text and data mining activities -- that is, the automated processing of digital materials to uncover new knowledge -- have become more frequent in all areas of scientific research. Because they require a massive use of copyrighted work, there are evident conflicts with copyright legislation. Countries at the forefront of research and development have begun to address this issue. This paper presents the basic aspects of legislation applicable to text and data mining activities. It offers a detailed comparative analysis of the norms of the main jurisdictions that have regulated them to date, highlighting in each case the positive and negative aspects. An adequate knowledge of these laws is not only important for researchers but also important for the academic librarians who provide advice and support in these matters.

In recent decades, higher education institutions around the world have come to depend on complex digital infrastructures. In addition to registration, financial, and other operations platforms, digital classroom tools with built-in learning analytics capacities underpin many course delivery options. Taken together, these intersecting digital systems collect vast amounts of data from students, staff, and faculty. Educators' work environments--and knowledge about their work environments--have been shifted by this rise in pervasive datafication. In this paper, we overview the ways faculty in a variety of institutional status positions and geographic locales understand this shift and make sense of the datafied infrastructures of their institutions. We present findings from a comparative case study (CCS) of university educators in six countries, examining participants' knowledge, practices, experiences, and perspectives in relation to datafication, while tracing patterns across contexts. We draw on individual, systemic, and historical axes of comparison to demonstrate that in spite of structural barriers to educator data literacy, professionals teaching in higher education do have strong and informed ethical and pedagogical perspectives on datafication that warrant greater attention. Our study suggests a distinction between the understandings educators have of data processes, or technical specifics of datafication on campuses, and their understanding of big picture data paradigms and ethical implications. Educators were found to be far more knowledgeable and comfortable in paradigm discussions than they were in process ones, partly due to structural barriers that limit their involvement at the process level.

In this article the authors respond to a comment on their article "An Analysis of the Labor Market for Uber's Driver-Partners in the United States," in the 2017 issue of the journal. Topics include the criticism based on the use of outdated data and selective reporting of findings, and the invitation language makes no mention of a connection between the survey and Uber Technologies.

Purpose: The purpose of this paper is twofold: to discuss methodological challenges facing US scholars when conducting international research; and to present personal reflections as educational leadership faculty in the USA conducting and publishing on research undertaken in Haiti and Thailand. Design/Methodology/Approach: This study drew from educational leadership literature and personal experiences to identify methodological challenges to conducting and publishing international research in the field of educational leadership. Findings: The methodological challenges facing international research--language, data, publication, and career incentives--should not be reasons to hinder scholars from conducting research in international contexts. Allowing methodological deterrents to impede international research limits US scholar engagement in global conversations and places the field of educational leadership in the USA at risk of a parochial and myopic future. Originality/Value: This paper explores the methodological reasons as to why US scholars are not engaging in international research and provides two vignettes of faculty research in international contexts. This discussion is valuable for faculty interested in or presently conducting research beyond US borders.

This paper uses methods derived from the field of futures studies to explore the future of technology-enhanced assessment. Drawing on interviews and consultation activities with experts, the paper aims to discuss the conditions that can impede or foster "innovation" in assessment and education more broadly. Through a review of relevant research, the paper suggests an interpretive model of the factors sustaining the conservatism of educational assessment: the utilitarian view of education, dominant beliefs about academic excellence, and market or quasi-market dynamics. In the central section of the paper, three scenarios of innovation in assessment are described, developed through an iterative process involving researchers, representatives from the e-assessment industry, and experts from British awarding organisations. In the final section, a critical discussion draws attention to the implications that data pervasiveness and computer-generated predictive models may have for the future of education.

Purpose: Much of the recent research on data-driven decision making in US schools has focused on standardized test scores while other forms of data in schools have gone largely unexamined as useful data, such as teacher-assigned grades. Based on the literature, the theory outlined in this paper is that grades, as data historically overlooked in schools, are a useful multidimensional assessment for decision making by educational leaders. This paper aims to address these issues. Design/methodology/approach: Using multidimensional scaling, grades, and standardized test scores are compared for 195 students in grades 9-12 from two US school districts. The relationship between these assessments is visualized between grades in core subjects, such as Mathematics and English, non-core subjects, such as Art and Physical Education, and standardized test scores, such as the ACT. Findings: Two significant dimensions appear to be embedded within grades; assessment of academic knowledge and an assessment of a student's ability to negotiate the social processes of school. These findings indicate that grades should be reconceptualized as informative for data-driven decision making in schools as a potential assessment of both academic knowledge and a student's ability to negotiate the social processes of school. Originality/value: Grades have been overlooked as useful data in the data-driven decision-making literature. This paper provides novel evidence for the usefulness of actual teacher-assigned grades in school and district decision making as well as research and policymaking versus the past use of student self-reported grades or teacher perceptions of grading practices. (Contains 2 figures.)

Data have long been considered a key factor in organizational decision-making (Simon, 1955; Lindblom & Cohen, 1979). Data offer perspective, guidance, and insights that inform policy and practice (Newell & Simon, 1972; Kennedy, 1984). Recently, education policymakers have invested in the use of data for organizational improvement in states and districts with such initiatives as Race to The Top (United States Department of Education, 2010) and the development of statewide longitudinal data systems (Institute for Education Sciences, 2010). These and other initiatives focus attention on how data can be used to foster learning and improvement. In other fields, including economics and business, much work has been done to identify leading indicators that predict organizational outcomes. In this paper, we conceptualize how leading indicators might be used in education, using examples from a small sample of school districts with reputations as strong users of data. We define leading indicators as systematically collected data on an activity or condition that is related to a subsequent and valued outcome, as well as the processes surrounding the investigation of those data and the associated responses. Identifying leading indicators often prompts improvements in a district's system of supports. To develop this concept, we describe four examples of how districts identified and used key indicators to anticipate learning problems and improve student outcomes. We also describe the infrastructure and other supports that districts need to sustain this ambitious form of data use. We conclude by discussing how leading indicators can bring about more intelligent use of data in education.

This paper reports provisional Australian comparison data and scoring instructions for the "Test of Word Reading Efficiency" (TOWRE). The TOWRE is a popular reading fluency test used in reading research, classroom assessment and clinical practice. Approximate "norms" were obtained from children attending four primary schools in New South Wales. Results suggested that the US norms for the TOWRE may overestimate the reading level of Australian children in lower grades and that the performance on the two parallel forms (A and B) of the subtests ("Sight Word Efficiency and Phonemic Decoding Efficiency") of the TOWRE did not differ from each other. While no performance differences were found between boys and girls overall, it was noted that the youngest boys outperformed the youngest girls on Form A of the Sight Word Efficiency subtest, and the youngest girls outperformed the youngest boys on Form B of the Sight Word Efficiency subtest. Limitations of the current study are discussed and a brief reference is made to a new (2012) edition of TOWRE (TOWRE-2).

Like many parents and educators, the author is concerned about both quality and equity in the school systems and schools, public and private. He is equally frustrated at the seemingly zealous focus on producing more and more charter schools when America have had: (1) limited success in that arena; and (2) limited data on their success. That stated, he finds value in the charter experiment. He thinks it is helpful to find out-of-the-box ideas of educational reform. However, he is challenged when he senses a need to grow more and more charters when data show that they perform largely lesser than other public schools. They can be dressed up, but if they look and feel like the lowest-performing schools, guess what? They'll be low performing, too. The author always finds it interesting that a bunch of community and business people can come in and think they build a better school than the bunch with education credentials. Sometimes they can. Most of the time they fail miserably because they are in way over their pay grade with respect to educational pedagogy. Of course, the real problem is that there are too many underperforming, out-moded, and under-talented schools. These are the bad schools, and the word bad is fitting. Over 55 million students are taught in K-12 public and private schools in the United States annually. The sheer scope of this issue is hard to fathom. Nevertheless, it is a critical issue that must be contended with in America, and the charter discussion is an important piece of that discussion. In this article, the author makes a few targeted points about Dr. Maranto's review of his edited book, "Finding Superman: Debating the Future of Public Education in America" (2012). (Contains 2 notes.)

Poverty is generally defined as income or expenditure insufficiency, but the economic condition of a household also depends on its real and financial asset holdings. This paper investigates measures of poverty that rely on indicators of household net worth. We review and assess two main approaches followed in the literature: income-net worth measures and asset-poverty. We provide fresh cross-national evidence based on data from the Luxembourg Wealth Study. (Contains 3 figures, 6 tables, and 16 footnotes.)

The author achieved something that he had been striving to do for several semesters when, in 2002, he revised his survey course on the history of the United States up to Reconstruction by replacing most of the photocopied readings he had assigned in the past with online texts. Readings on the web now provided the basis for 10 of the 12 weekly tutorial discussions in the course, as well as for six of the 10 essay questions. Not only did using online material allow him to assign sources that he would not otherwise have been able to provide to students, it reduced the size and cost of the course reader, and relieved the strains on the library system created by over a hundred students seeking the same texts. He felt confident that his students would be just as enthusiastic about a larger online component in the course. However, he was wrong. In this article, the author discusses the negative reactions and complaints of students towards online readings. Student reactions to online materials should certainly introduce a note of caution into the rush to use computers and the web to deliver course readings. However, historians should respond not by turning their back on that medium, but by looking more closely at its properties, and the expressive, rather than additive, possibilities that they offer. (Contains 37 notes.)

Seeds and other plant materials in seed and gene bank collections are rarely considered adequately conserved today unless genetically identical duplicate samples have been created and safely stored elsewhere. This paper explores the history of seed banking to understand how, why and with what consequences copying collections came to occupy this central place. It highlights a shift in the guiding metaphor for long-term preservation of seed collections, from banking to backup. To understand the causes and consequences of this shift in metaphor, the paper traces the intertwined histories of the central long-term seed storage facility of the United States (opened in 1958) and the international seed conservation system into which that facility was integrated in the 1970s. This account reveals how changing conceptions of security, linked to changing economic, political and technological circumstances, transformed both the guiding metaphors and the practices of seed conservation in these institutions. Early instantiations of long-term cold storage facilities vested security in robust infrastructures and the capacities of professional staff; between the 1960s and 1990s, this configuration gave way to one in which security was situated in copies rather than capacities. This observation ultimately raises questions about the security promised and achieved through present-day infrastructures for crop genetic resources conservation. [ABSTRACT FROM AUTHOR]

This paper aims to point out that the publication of the five volumes by Thomas and Znaniecki The Polish Peasant in Europe and America opened new scenarios, and gave its fundamental contribution in authorising a new way of conducting researches, which voluntarily distances from the 'scientistic logic' to recognise the heuristic-interpretative value of narration, though without denying the usefulness of the quantitative approach. That being stated, the specific purpose of this paper is twofold: focusing on the heuristic-interpretative value of narration while reconstructing, at the same time, the common thread that, starting from The Polish Peasant in Europe and America, connects apparently distant texts and authors stimulating a reflection on the development of empirical research and on its future. [ABSTRACT FROM AUTHOR]

In the twenty-first century, voter choice and the broader political debate are within the reach of those that can access and channel the vast streams of user data that are generated online. How digital platforms utilize personal user data to influence the outcome of democratic processes has become a central issue that liberal democracies must confront. The paper explores whether competition law has a role to play when it comes to addressing this intersection of Big Tech, data, and democracy. It first sets out the democratic roots of competition or antitrust law in the United States and the European Union. From these, the paper deduces that competition law cannot remain inactive when it comes to maintaining a democratic society in the face of the abilities of Big Tech to influence democratic processes and outcomes. The paper then goes a step further and asks what role competition law could play in this regard. Should democratic values simply be reflected in the procedural set-up of antitrust law, or is there a role for democratic values in the substantive provisions as well? And if so, does antitrust law's focus on keeping market power in check suffice to fulfill its role in a democratic society, or does this role require the law to specifically target antidemocratic market behavior as anticompetitive harm? In navigating these questions, the paper contributes to the ongoing debate on political antitrust and sets out an ambitious research agenda on how to carry this discussion forward. [ABSTRACT FROM AUTHOR]

Copyright of Estonian Journal of Archaeology is the property of Teaduste Akadeemia Kirjastus and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper uses a dynamic stochastic general equilibrium (DSGE) model to explore additional information that can be extracted from the yield curve about the Federal Reserve's implicit inflation target. In the model, monetary policy follows a nominal interest rate rule with a drifting inflation target, and agents have imperfect information about the persistent component of the inflation target. When the yield curve information is included, the DSGE model generates inflation expectations that are highly correlated with survey data evidence. In the DSGE model, agents quickly learn the inflation target and the gap between the perceived target and the actual target is quantitatively small. This is in contrast to some existing studies that suggest a persistent role of imperfect information even as long-run inflation expectations have declined and stabilized at a low level since the mid 1980s. [ABSTRACT FROM AUTHOR]

This paper examines how participatory inequalities are (re)produced in eDeliberation, a practice that purposely fosters open, fair, and rational discussions among citizens over the Internet. Relying on the theoretical traditions of Bourdieu's capital and actor-network theory, this paper proposes that technical capital, along with social, economic, cultural, and symbolic capital, function in eDeliberation as inequality makers. Two cases of eDeliberation practices conducted in the United States serve as the sources of data. Both statistical analyses of close-ended questions and a qualitative content analysis of open-ended questions from surveys were used to generate the empirical findings. Technical capital is found to reproduce existing inequalities through the unequal accumulation rates and the unbalanced convertibility associated with different actors. Both theoretical and practical implications of the findings are suggested. [ABSTRACT FROM AUTHOR]

Since the early 1990s, the internet has dominated the attention of the media, academics and business organizations. It has the potential of being a revolutionary way to collect primary and secondary data, although much more research is needed to learn how to better harness its strengths. This project compares depth interviews collected online with depth interviews conducted face-to-face. Advantages and disadvantages are highlighted, as well as suggested strategies for successfully collecting online data. Major points are illustrated using data from a project in which both data collection techniques are employed. The online interview dataset included some of the strongest and some of the weakest interviews in the investigation. This paper argues that under some conditions online depth interviews can provide a useful complement to the traditional face-to-face interview. Sampling frame problems of nonrepresentativeness, endemic in quantitative online data collection, is not problematic if the researcher is conducting an interpretive investigation. When the researcher's goal is not to quantify or generalise but instead to better understand a particular population, online data collection can complement other datasets, allow data triangulation and strengthen the trustworthiness of the findings. [ABSTRACT FROM AUTHOR]

This paper explores how data-driven practices and logics have come to reshape the possibilities by which the teaching profession, and teaching professionals, can be known and valued. Informed by the literature and theorising around educational performativity, the constitutive power of numbers, and affective responses to data, it shows how different US educators experienced, and came to embody, new forms of numbers-based accountability. Drawing on interviews with teachers, and school- and district-level leaders, as well as relevant school-based documents, it is argued that such data are now both effective (i.e. they change 'what counts' within the profession) and affective (i.e. they produce new expectations for teachers to profess data-responsive dispositions over actual educative practices). This prevalence and use of data have combined not only to change teaching into a 'data profession', but also to change teachers into 'professors' of data. [ABSTRACT FROM AUTHOR]

The ability to identify which factors best capture systematic return covariation is central to applications of multifactor pricing models. This paper uses a common data set to evaluate the performance of various proposed factors in capturing return comovements. Factors associated with the market, size, past return, book-to-market, and dividend yield help explain return comovement on an out-of-sample basis (although they are not necessarily associated with large premiums in average returns). Except for the default premium and the term premium, macroeconomic factors perform poorly. We document regularities in the behavior of the more important factors, and confirm their influence in the Japanese and U.K. markets as well. [ABSTRACT FROM AUTHOR]

The United States (US) federal government allocates hundreds of billions of dollars to provide resources to Americans with disabilities, older adults, and the poor. The American Community Survey (ACS) influences the distribution of those resources. The specific aim of the project is to introduce health researchers to Public Use Microdata Sample file from 2009 to 2011. The overall goal of our paper is to promote the use of ACS data relevant to disability status. This study provides prevalence estimates of three disability related items for the population at or over the age of 15 years who reside in one of the continental states. When population weights are applied to the 7,198,221 individuals in the sample under analysis, they are said to represent 239,641,088 of their counterparts in the US population. Detailed tabulations by state (provided as Microsoft Excel® spreadsheets in ACS output) clearly show disability prevalence varies from state-to-state. Because analyses of the ACS data have the ability to influence resources aiding individuals with physical mobility challenges, its use should be promoted. Particular attention should be given to monetary allocations which will improve accessibility of the existing built environment for the individuals with mobility impairment. [ABSTRACT FROM AUTHOR]

. The paper considers the use of level-of-effort (LOE) paradata to model the non-response mechanism in surveys and to adjust for non-response bias, particularly bias that is missing not at random or non-ignorable. Our approach is based on an unconditional maximum likelihood estimation (call-back) model that adapts and extends the prior work to handle the complexities that are encountered for large-scale field surveys. A test of the 'missingness at random' assumption is also proposed that can be applied to essentially any survey when LOE data are available. The non-response adjustment and the test for missingness at random are then applied and evaluated for a large-scale field survey-the US National Survey on Drug Use and Health. Although evidence on non-ignorable non-response bias was found for this survey, the call-back model could not remove it. One likely explanation of this result is error in the LOE data. This possibility is explored and supported by a field investigation and simulation study informed by data obtained on LOE errors. [ABSTRACT FROM AUTHOR]

This paper reports on part of a larger study investigating the role of phonemic awareness (PA) and decoding ability in second language (L2) reading development among adult English language learners who have not mastered reading in their native language. The data reported in this paper were part of a larger longitudinal study that investigated a variety of factors related to initial reading development for adult L2 learners of English. A group of 26 participants enrolled in adult ESL education classes in the United States were followed for one year and assessed on measures of phonemic/phonological awareness and decoding ability. The results of this study document the relationship between phonemic/phonological awareness and L2 beginning reading in English for adult learners and provide evidence for similar relationships existing between phonemic/phonological awareness and early reading for adult learners and children learning to read in English. While reading and literacy development are complicated, the findings of this study suggest the importance of the decoding process for adult learners in the beginning stages of ESL reading. [ABSTRACT FROM AUTHOR]

Technologies that deploy algorithmic calculation are becoming ubiquitous to the homeland securitization of the war on terror. From the surveillance networks of the city subway to the biometric identifiers of new forms of border control, the possibility to identify “association rules” between people, places, objects and events has brought the logic of pre-emption into the most mundane and prosaic spaces. Yet, it is not the case that the turn to algorithmic calculation simply militarizes society, nor even that we are witnessing strictly a commercialization of security. Rather, algorithmic war is one form of Foucault's sense of a “continuation of war by other means”, where the war-like architectures of self/other, here/there, safe/risky, normal/suspicious are played out in the politics of daily life. This paper explores the situated interplay of algorithmic practices across commercial, security, and military spheres, revealing the violent geographies that are concealed in the glossy techno-science of algorithmic calculation. [ABSTRACT FROM AUTHOR]

Receiver operating characteristic (ROC) analysis has been used in a variety of settings since it was first declassified by the United States government over 60 years ago. One venue in which it has received particular attention is in the field of radiology. In radiology, as in other areas of application, ROC analysis is used to assess the ability of a diagnostic test to distinguish between two opposing states. One useful descriptor in ROC analysis is the area under the ROC curve. At times, it is useful and insightful to average ROC curves in order to create a single curve that summarizes all of the data from multiple readers. In this paper, we investigate the impact of correlated readings on the average area under two readers' ROC curves using several common averaging strategies, and then apply the results to a radiologic study. [ABSTRACT FROM AUTHOR]

Longitudinal zero-inflated count data arise frequently in substance use research when assessing the effects of behavioral and pharmacological interventions. Zero-inflated count models (e.g. zero-inflated Poisson or zero-inflated negative binomial) with random effects have been developed to analyze this type of data. In random effects zero-inflated count models, the random effects covariance matrix is typically assumed to be homogeneous (constant across subjects). However, in many situations this matrix may be heterogeneous (differ by measured covariates). In this paper, we extend zero-inflated count models to account for random effects heterogeneity by modeling their variance as a function of covariates. We show via simulation that ignoring intervention and covariate-specific heterogeneity can produce biased estimates of covariate and random effect estimates. Moreover, those biased estimates can be rectified by correctly modeling the random effects covariance structure. The methodological development is motivated by and applied to the Combined Pharmacotherapies and Behavioral Interventions for Alcohol Dependence (COMBINE) study, the largest clinical trial of alcohol dependence performed in United States with 1383 individuals. [ABSTRACT FROM AUTHOR]

The deep sea has a large strategic depth, in which target detection is a crucial link, that is, how to detect the target submarine. For this reason, since this century, countries represented by the United States have innovated ideas, innovated underwater detection technology, and enhanced new underwater detection capabilities. In this paper, by consulting more than 100 literatures, the data acquisition technology in underwater acoustic detection in recent years has been investigated in detail, passive detection and active detection have been comprehensively reviewed, and the collaborative detection technology has also been summarized. In order to provide reference for related research. [ABSTRACT FROM AUTHOR]

This paper details the process and results from the first step of a three-step research process. This first step looks to identify the most predictive pre-retrofit metric of energy consumption to utilize in a model to predict the energy savings post retrofit. The ultimate goal of this research is to predict candidacy for retrofit using only a combination of demographic and home-characteristics data that is available for the entirety of the U.S. residential housing stock. This is important, as utility data is almost always protected for privacy and thus unavailable to assist in targeting where energy efficiency retrofits will be successful. It is found that the best metric is the simplest, total energy consumption divided by total floor area. In addition to evaluating which pre-use metric is most indicative of post retrofit savings, the paper evaluates the endogenous component of pre-use to post use and a potential method to alleviate this endogeneity. The research finds that by removing the year that is used to calculate the savings as the baseline pre-use year removes a portion of the endogeneity. It is also found that one year before the savings base year is the best year to utilize as the base. [ABSTRACT FROM AUTHOR]

The existence of water markets establishes water prices, promoting trading of water from low- to high-valued uses. However, market participants can face uncertainty when asking and offering prices because water rights are heterogeneous, resulting in inefficiency of the market. This paper proposes three random forest regression models (RFR) to predict water price in the western United States: a full variable set model and two reduced ones with optimal numbers of variables using a backward variable elimination (BVE) approach. Transactions of 12 semiarid states, from 1987 to 2009, and a dataset containing various predictors, were assembled. Multiple replications of k-fold cross-validation were applied to assess the model performance and their generalizability was tested on unused data. The importance of price influencing factors was then analyzed based on two plausible variable importance rankings. Results show that the RFR models have good predictive power for water price. They outperform a baseline model without leading to overfitting. Also, the higher degree of accuracy of the reduced models is insignificant, reflecting the robustness of RFR to including lower informative variables. This study suggests that, due to its ability to automatically learn from and make predictions on data, RFR-based models can aid water market participants in making more efficient decisions. [ABSTRACT FROM AUTHOR]

While there has been an increasing awareness among policy makers and the public about the potential risks of financial exploitation faced by the elderly, there have been few national assessments of this problem due largely to methodological challenges-such as underreporting, small and nonrepresentative samples, inconsistent offense definitions, and infrequent or unsystematic data collection. This paper illustrates the extent to which the National Incident-Based Reporting System (NIBRS) data can address some of these methodological limitations in order to contribute to a baseline picture of the prevalence and characteristics of elderly financial exploitation in the United States. [ABSTRACT FROM AUTHOR]

Numerous countries have recognized the need for improved surveillance data on the health of persons with intellectual and developmental disabilities (IDD). Federal agencies need additional information about the prevalence and health of persons with IDD to guide decisions about policies and programs. Without such data, health inequities and health needs of people with IDD can go unrecognized and be ignored, and resources may be misdirected. The priority areas for needed information, however, have not been well documented. To determine priorities for health data for persons with IDD, we conducted focus groups with three types of stakeholders from around the United States: researchers/practitioners, adults with IDD, and family members. Focus group dialogue was coded for themes and compared across stakeholder categories. Themes common to all groups included valuing people with IDD and respecting their self‐determination; affirming the need for data including longitudinal data; holding a holistic view of physical, mental, social, and sexual health; and access to quality health care, medications, and assistive equipment. Each group also contributed unique ideas such as importance of trust for disclosure of private information, stereotypes and discrimination, and social influences on health. Stakeholders identified specific health conditions to monitor, including COVID‐19. Findings have implications for establishing a health surveillance data system and for practice more generally. Health needs to be considered holistically, including physical, mental, social, and sexual health. A data framework needs to extend beyond a cross‐sectional comparative framework to include longitudinal tracking and monitoring conditions unique to persons with IDD. People with IDD may not trust nor disclose sensitive information about their disability and health to support persons and surveyors, which has implications for under‐reporting of prevalence of IDD and validity of proxy‐reporting. Input from multiple stakeholders is fundamental to developing a usable and relevant data collection system. [ABSTRACT FROM AUTHOR]

This paper examines the politicization of gender inequality through a cross-national analysis of attitudes towards inequality between men and women. The data were obtained from national surveys in the United States, Britain, West Germany, Australia and Italy. In all of these countries, attitudes towards gender inequality were found to be associated with the 'left- right' cleavage over economic inequality and redistribution, but they were unrelated to 'new politics' issues. It was also found that attitudes towards gender inequality were more closely integrated into the left-right cleavage in those countries where there was greater awareness of gender issues, and that they had very little net impact on partisanship. Thus high levels of awareness of gender inequality are not associated with the emergence of a new cross-cutting political cleavage. It is concluded that inequality of opportunity between men and women does not constitute part of a new politics agenda, nor does it cross-cut other sources of political interests. It is more plausibly seen as a new element of the well-established left-right cleavage. Consequently, it leaves the structure of political divisions relatively intact. [ABSTRACT FROM AUTHOR]

For decades, the United States has been generally excluded from cross-national quantitative datasets on the study of collective action and political resistance. More recently, however, new data collection efforts are on the rise. These projects specifically focus on gathering granular level information about street protests and mobilizations in the United States. In this article, we conduct a rigorous exploratory data analysis of three contemporary protest datasets. These data collect information about the when, where and how of contentious politics in the United States. Our thorough data review first summarizes the key similarities and differences across the datasets. Next, we review the regional, temporal and methodological strengths and weaknesses of each dataset both individually and in contrast to one another. Last, we examine potential research applications of these data by demonstrating what these data reveal about the risks of protesting in these types of events. We conclude by offering recommendations for data use and future data collection strategies for the study of collective action. [ABSTRACT FROM AUTHOR]

The article offers the author's insights on the study "Hierarchical Bayesian auto-regressive models for large space time data with applications to ozone concentration modelling," by Sujit Kumar Sahu and Khandoker Shuvo Bakar. The author notes that the application to ozone concentration and air pollution using data from the eastern U.S. is a useful exercise. The author expects that the paper will help and motivate new research on large spatio-temporal multivariate data sets.

Copyright of Contemporary Accounting Research is the property of Canadian Academic Accounting Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)