Federal Data Research Articles

Utilizing Federal Data Sources to Support Nursing Workforce Analysis.

Effective health workforce analysis requires robust data and information. Quality data facilitate monitoring workforce trends, identifying shortages, forecasting employment needs, and planning educational programs. A wide range of federal agencies collect various forms of data, including administrative data, surveys, and censuses, which can be used for health workforce analysis. However, identifying the most appropriate data sources to address a specific nursing workforce issue can be challenging, particularly for newcomers to the field or those researching unfamiliar topics. In this article, we introduce and review 18 federal data sources pertinent to nursing workforce analysis. We categorize the datasets by their associated federal agency, describe each source, discuss their applicability to nursing workforce studies, present examples of past studies that employed these datasets, and highlight their limitations. Our aim is to help researchers, policymakers, and healthcare administrators efficiently locate and leverage relevant data for their analysis.

Native Faculty in Library and Information Science, 1990–2022

We assessed the representation of Native faculty in LIS programs from 1990 to 2022. We comparative representation in LIS against trends in postsecondary education in the U.S. We utilized ALISE and federal data sources. We found that in both fields, Native faculty held lower ranking positions, predominantly as assistant professors. We also revealed that the quantity of Native LIS faculty was extremely low throughout the period assessed, with the possibility of a very few outlier LIS programs driving national statistics. Our study suggests that factors affecting representation of Native faculty in LIS might be similar to those in postsecondary education.

Unemployment and Personal Income Loss After Traumatic Brain Injury

Employment and personal income loss after traumatic brain injury is a major source of postinjury stress and a barrier to societal reintegration. The magnitude of labor market ramifications following traumatic brain injury remains largely unknown. To quantify the 3-year postinjury labor market consequences following traumatic brain injury in Canada. To also estimate the incurred national labor market cost over the study period. This retrospective quasi-experimental, pan-Canadian observational cohort study used linked administrative health and federal taxation data obtained between 2007 and 2017. Mixed-effects difference-in-difference regressions were constructed to estimate the annualized magnitude of the personal income and employment loss during each of the 3 years following injury, respectively, relative to preinjury baseline. Participants included tax-filing adult (19 to 61 years old) traumatic brain injury survivors. Traumatic brain injury. Coprimary outcomes were personal income loss and the proportion of newly unemployed individuals per annum. Secondary objectives were to quantify income and employment loss within mild, moderate, and severe traumatic brain injury subgroups. A total of 18 050 patients with traumatic brain injury between 2007 and 2017 were identified (mean age, 38.0 [SD, 12.4] years; 13 360 male [74.0%]), each of whom was followed up with for 3 consecutive fiscal years. Mean income was CAD $42 600 (US $31 083) in the fiscal year prior to injury and 82% were employed at time of injury. The adjusted mean loss of personal income was CAD $7635 (US $5650) in the first year after injury (Y+1) and CAD $5000 (US $3700) in the third year after injury (Y+3) relative to uninjured controls. In each of the 3 postinjury years, 7.8% individuals were newly unemployed compared with the preinjury baseline. The adjusted average personal income loss for mild, moderate, and severe traumatic brain injury subgroups were CAD $3354 (US $2482), CAD $6750 (US $4995), and CAD $17 375 (US $12 859), respectively, at Y+3; the proportion of unemployed individuals increased by 5.8%, 9.2%, and 20% across the same groups at Y+3 after injury relative to preinjury baseline. The estimated total reduction in personal income aggregated over the 3 postinjury years for the affected participants was CAD $588 million (US $435 million). This work represents national cohort data quantifying the labor market implications of traumatic brain injury. These results may be used to inform economic evaluations and social service resource allocation.

US urban land-use reform: a strategy for energy sufficiency

Policy approaches to the global energy transition often focus on technology-based solutions while ignoring challenges of overall energy demand. A sufficiency-first approach aims to limit superfluous consumption while achieving wellbeing for all. This study focuses on US built environment mechanisms of sufficiency under urban land-use policy. The historical context of US exclusionary and car-oriented planning is reviewed with an order-of-magnitude assessment of the effects on greenhouse gas emissions (GHGE). Using national vehicle-miles traveled (VMT) data derived from mobile device locations (Replica) and validated here with federal data, a hypothetical scenario explores the potential for state urban land-use reforms to enable energy sufficiency. Tenth percentile-VMT (per capita) neighborhoods are defined by state: in 47 states, the typical such neighborhood has less than 33% of its housing units in structures larger than four units. Assuming each state redresses its housing shortage while matching this VMT, 31 Mt CO2e (direct GHGE) and about 38 Mt CO2e (indirect and life-cycle GHGE) would be avoided in 2033. Texas, California, and Florida have the largest absolute emissions reduction opportunity. Urban land-use reforms comprise a logical starting point for a US sufficiency agenda. Key priorities for research, data collection, and technology and policy innovation are proposed. Policy relevance International climate policy is increasingly focused on enabling people to consume less energy: not just technological ‘efficiency’ but ‘sufficiency’ is needed. However, sufficiency has seen little uptake in the US. It may be more relevant to US policymakers if related to the growing momentum for reforming land-use planning and housing policy to address the housing shortage and affordability crisis. This crisis stems in part from the US prevalence of single-family zoning and car-centric planning, rooted in a history of racial segregation; these same laws effectively mandate people to maintain more polluting lifestyles. This study estimates how much climate pollution could be avoided with state-led land-use reform. If states committed to solving the housing shortage while building new housing in neighborhoods where people can drive less, the savings could be comparable with expanding electric vehicle policies. Policymakers and practitioners can enable these reforms while supporting complementary policy goals.

The impact of internal labor migration on morbidity rates with temporary disability in the Russian Federation

Introduction. One of the most important indicators of the health of the working population is the incidence of temporary disability. The statistical data do not take into account the temporary labor migration of the population, which distorts the idea of the morbidity of the permanent population at the level of the subjects of the Russian Federation and municipalities. The study aims to carry out a comparative assessment of the temporary disability (ТD) level and rating places of the subjects of the Russian Federation on the basis of statistical indicators "Number of cases of TD" and "Number of days of TD" per 100 employees and calculated indicators per 100 employed in the economy. Materials and methods. The article tells about the use of federal statistical observation data. Specialists have made their own calculations of indicators of the level of temporary disability by the number of cases and days per 100 employed in the economy. A direct ranking was carried out in descending order of all the studied indicators. The authors also conducted a direct ranking in descending order of all the studied indicators and performed a comparative analysis of the rating places of the subjects of the Russian Federation according to the level of temporary disability, according to official statistical data per 100 employees and calculated data per 100 employed. Results. In almost 30% of the subjects of the Russian Federation, significant changes were detected in 20 or more rating places, both with the shift of regions into groups with higher levels and with lower levels of morbidity. Limitations. The materials used in this study did not take into account the gender and age characteristics of morbidity. Conclusion. At the present stage, it is necessary to develop new methodological approaches for the analysis of the temporary disability at the regional and municipal levels, their introduction into the system of social and hygienic monitoring and the system of risk management for public health. The use of the indicator "number of people employed in the economy" to analyze temporary disability at the territorial (regional, municipal) level more accurately reflects the level of morbidity of the permanent population living in the study area. Ethics. The conclusion of the local Ethics Committee is not required for conducting the study.

Principal Leadership of Pre-K Programs in Elementary Schools: Evidence from North Carolina

Pre-Kindergarten (Pre-K) programs are becoming increasingly common in elementary schools across the United States—in fact, a recent analysis of federal data revealed that 57% of public schools have a Pre-K grade. Despite the prevalence of Pre-K programs in schools, principals—known to be among the most important factors in school success—often lack the knowledge and professional supports to effectively lead Pre-K programs. In this study, guided by sensemaking theory, we work to advance knowledge on Pre-K principal leadership through a sequential mixed-methods analysis of elementary school principals in the state of North Carolina. Our study includes a statewide survey of all lead and assistant principals in the state ( N = 520) as well as follow-up interviews with 27 of the surveyed principals. Our findings reveal that while they report strong conceptual support for the Pre-K programs in their schools, principals demonstrate limited engagement with them. We also find that principal background and preparation in early education and the proportion of students from a Pre-K program that ultimately enroll in the school for kindergarten are important factors that help explain variation in principal orientations to Pre-K leadership.

National Center for Health Statistics Data Linkage Program: Generating Synthetic Data to Support Tiered Access

The National Center for Health Statistics (NCHS) has a long-established data linkage program that links NCHS health survey data with vital and other administrative records to expand the analytic potential of both the survey and administrative data. Integrating survey and administrative data provides a powerful mechanism for creating policy-relevant data resources to support the examination of factors that can influence disability, chronic disease, health care utilization, morbidity, and mortality. However, data privacy concerns impact the accessibility of NCHS linked data and thus its utilization. Nearly all NCHS linked data files are available only through the NCHS and Federal Statistical Research Data Centers. To minimize this barrier to access, the NCHS Data Linkage Program is engaged in a pilot project to create NCHS' first public-use fully synthetic data files. This initiative supports Evidence Act requirements, including tiered access to federal data. The talk will include an overview of the steps taken to generate the synthetic linked data and provide a verification process to support its analytic utility. The talk will also include a summary of NCHS’ exploration of other privacy enhancing technologies to increase partnership and data access.

Attracting doctors to rural areas under the state program: performance indices

Introduction.The implementation of the state program “Zemsky Doctor” is one of the effective mechanisms to attract medical personnel to medical institutions located in rural areas. The purpose of the study. To analyze the indices for attracting doctors to medical institutionsss located in rural areas of the Russian Federation during Federal Research Institute for Health Organization and Informatics the period from 2015 to 2022 within the framework of the state program “Zemsky Doctor”. Materials and methods. The study used statistical data on eighty two subjects of the Russian Federation based on operational documented inquiries for the period from 2015 to 2022. Analytical and statistical methods were used in the research process. Descriptive statistics and correlation analysis was conducted using the Statistica package version 13.3. Results. During the study period, more than 33,000 physicians of various specialties were attracted and employed in rural areas. The index of the number of doctors attracted to rural areas under the program from 2015 to 2022 increased by 32.2%, from 0.9 to 1.19 per 10,000 rural population. When analyzing this index by regions of the Russian Federation, significant differences were revealed. Research limitations. The research materials are limited by the results of the analysis of quantitative data obtained as a result of an operational request to the subjects of the Russian Federation and statistical data of the forms of federal statistical observation. Conclusion. The study revealed the regions with the lowest level of the indice of physician supply also to have a low index of the number of doctors recruited under the program. The results of correlation analysis showed that in most of the Russian regions there is a direct dependence of the index of physician supply on the results of the implementation of the program “Zemsky Doctor”. The results of the program implementation have a significant impact on the staffing of medical organizations located in rural areas.

Association of Victimization by Sex among Public Facing Bus and Subway Transit Workers, New York City.

Federal data indicate that assaults on transit workers resulting in fatalities or hospitalizations tripled between 2008 and 2022. The data indicated a peri-pandemic surge of assault-related fatalities and hospitalizations, but assaults with less dire outcomes were not recorded. In collaboration with the Transport Workers Union, Local 100, we conducted an online survey in late 2023 through early 2024 of New York City public-facing bus and subway workers that focused on their work experiences during the 2020-2023 period of the COVID-19 pandemic. Items for this analysis on victimization included measures of physical and sexual assault/harassment, verbal harassment/intimidation, theft, and demographic characteristics (e.g., sex, race, work division). We estimated separate modified Poisson models for each of the four outcomes, yielding prevalence ratios (PRs) and 95% confidence intervals (CIs). Potential interactions between variables with strong main effects in the adjusted model were further examined using product terms. Among 1297 respondents, 89.0% reported any victimization; respondents also reported physical assault (48.6%), sexual assault/harassment (6.3%), verbal harassment/intimidation (48.7%), and theft on the transit system (20.6%). Physical assault was significantly more common among women in the bus division compared to female subway workers, male bus workers, and male subway workers (adjusted PR (aPR) = 3.54; reference = male subway workers; Wald test p < .001). With the same reference group, sexual assault/harassment was more frequently reported among female subway workers (aPR = 5.15; Wald test, p < .001), but verbal assault/intimidation and experiencing theft were least common among women in the bus division (aPR = 0.22 and 0.13, respectively; Wald tests, p < .001). These data point to the need for greater attention to record and report on victimization against workers in both buses and subway.

Reassessing the economy–environment tradeoff: do industry sectors, green jobs opportunities, and regulatory threats affect environmental concerns?

ABSTRACT Economic effects on environmental concerns assess macroeconomic pressures or microeconomic status differences but overlook environmental and labor scholarly attention to industry contexts. I test whether employed industry, green jobs opportunities, and regulatory threats influence five environmental concern indexes using cross-sectional US General Social Surveys from 2000, 2010, and 2021 and federal administrative data. Findings indicate individuals employed in resource extraction, construction, and manufacturing express less environmental concerns than service sector individuals but vary across dimensions. Resource extraction individuals express less concern for environmental protections and pollution harms. Manufacturing, construction and utilities individuals are less willing to sacrifice for the environment. Green jobs sub-industry employment is positively associated with more willingness to sacrifice and empowerment to act for the environment. Surprisingly, employment in Environmental Protection Agency regulated sub-industries is positively associated with more willingness to sacrifice for the environment. The findings underscore future research on how industry-based economic contexts shape environmental concerns.

Using GIS-based multicriteria decision analysis to prioritize invasive plant treatment: A creative solution for a pernicious problem

Invasive plant infestations are projected to rapidly increase with continued habitat fragmentation and climate change. The rate of spread often outpaces land managers’ ability to effectively detect and control infestations. Land stewards need tools that can match the rapid pace and scale of invasive infestations and help prioritize control efforts in the most ecologically important areas and optimize resource allocation. It is imperative that proposed control be informed by the best available ecological information. We present a spatially explicit modeling framework for prioritizing invasive plant treatment. In our case study from Michigan, we employ a multicriteria decision analysis model that synthesizes four critical factors for prioritizing invasive plant stewardship: integrity, biodiversity, resilience, and ecosystem services. Data for quantifying these factors were compiled from several state, federal, university, and non-governmental data sources. The model uses a geographic information system (GIS) to identify places that are impacted by invasive plant infestations that threaten to degrade ecosystem composition, structure, and function; are characterized by high ecosystem integrity; support high biodiversity; are resilient to disturbance; and provide ecosystem services. While specific to Michigan, our modeling framework is broadly applicable. This type of integrated analysis can help inform decisions about allocation of limited resources for numerous biodiversity stewardship and landscape-level conservation planning needs, regardless of geographic location.

The Steep Decline in Reporting to the National Practioner Data Bank, and a Look at Reporting Levels from “Plaintiff-Favorable” and “Defendant-Favorable” States

The establishment of the National Practitioner Data Bank (NPDB) was authorized in the Health Care Quality Improvement Act of 1986, and it mandated a federal database to collect information related to adverse actions initially against just physicians and dentists throughout the United States, including payments from malpractice lawsuits, restrictions on clinical privileges by hospitals, and medical licensure limitations and revocations by state licensing boards. The aggregate data reports made by this federal data bank began in 1991. The reporting level for the first ten years remained relatively stable in the nationwide range of 16,000 to 18,000 reports per year, but then a steady decline occurred over the second and third decades to under 8,000 reports per year by the year 2021. The researchers in this study explored a theory that might explain at least part of the drop in the states’ reporting levels. That is, states that could be called “Plaintiff-Favorable” (Arizona, Kentucky, New York, Pennsylvania, and Washington) would demonstrate a lesser rate of decline or even an increase in the reporting levels, and states that could be characterized as “Defendant-Favorable” (California, Michigan, Nevada, North Carolina, and Texas) would demonstrate a comparatively greater rate of decline in the reporting levels. The decline in reporting to the NPDB proved fairly consistent for both Plaintiff-Favorable and Defendant-Favorable states. The larger question as to why there occurred an overall negative trend in reporting to the NPDB across the United States during the second and third decades remains an intriguing area for future exploration.

In Case You Haven't Heard…

An increasing number of America's seniors are struggling with mental health issues, the senior living resource, Seniorly.com, reported. Compared to all other age groups, seniors aged 65 and older experienced the sharpest rise in mental health diagnoses between 2019 and 2023, according to an analysis by FAIR Health, a health care price data sharing consortium. For many seniors, mental health concerns have not subsided in 2024. To identify the best and worst states for seniors' mental health, Seniorly measured the most recent federal data across all 50 states and Washington, D.C. They found that Utah is the best state for seniors — 71.2% of older adults in Utah said they get enough social and emotional support — one of the highest rates in the U.S. — and they're unlikely to live alone (30.6%). The rest of the top five — Hawaii, Minnesota, South Dakota and Alaska — have their own strengths and weaknesses, but generally boast few mentally unhealthy days per month and lower depression rates than the rest of the country. Louisiana is the worst state: Older adults have an average of 3.9 mentally unhealthy days per month in Louisiana, the highest rate in the U.S. The rest of the bottom‐ranked states are geographically concentrated — Tennessee, Alabama, West Virginia and Oklahoma — and tend to have fewer mental health specialists available and higher depression rates among seniors.

Disparities in Cancer Mortality among Disaggregated Asian American Subpopulations, 2018-2021.

Federal, state, and institutional data collection practices and analyses involving Asian Americans as a single, aggregated group obscure critical health disparities among the vast diversity of Asian American subpopulations. Using from the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) Underlying Causes of Death database, we conducted a cross-sectional study using data on disaggregated Asian American subgroups (Asian Indian, Chinese, Filipino, Japanese, Korean, Vietnamese, other Asians) between 2018 and 2021. We examine deaths from 22 cancer types and in situ, benign neoplasms, identified using ICD-10 codes C00-C97 and D00-D48. Overall, our study comprised 327,311 Asian American decedents, with a mean age of death at 70.57years (SD=2.79), wherein females accounted for approximately half of the sample (n=36,596/73,207; 49.99%). Notably, compared to the aggregated Asian American reference group, we found higher proportions of deaths from total cancers among Chinese (25.99% vs. 22.37% [ref]), Korean (25.29% vs. 22.37% [ref]), and Vietnamese (24.98% vs. 22.37% [ref]) subgroups. In contrast, total cancer deaths were less prevalent among Asian Indians (17.49% vs. 22.37% [ref]), Japanese (18.90% vs. 22.37% [ref]), and other Asians (20.37% vs. 22.37% [ref]). We identified further disparities by cancer type, sex, and age. Disaggregated data collection and analyses are imperative to understanding differences in cancer mortality among Asian American subgroups, illustrating at-risk populations with greater granularity. Future studies should aim to describe the association between these trends and social, demographic, and environmental risk factors.

Perspectives on using Protected Species Observer (PSO) data to fill knowledge gaps about marine species distributions and habitat use

Abstract Responsible offshore wind energy development requires addressing knowledge gaps of marine mammal distribution and response to wind energy development. Data collected by Protected Species Observers (PSOs) could help fill these gaps if they were used to fit species distribution models. However, because PSO data are not systematically collected, a critical exploration of their potential utility is needed. We reviewed PSO data collected during offshore wind geophysical surveys. Our intention was to compare predictions from two species distribution models—one model fit with systematically collected data and the second model fit with PSO data. However, developing a model using the PSO data was impossible due to data collection and reporting procedures. Therefore, we reframed our question to “What changes would be necessary for PSO data to be used to understand species distributions?” We compared PSO data with data collection fields recommended by US federal agencies and data collection requirements in Marine Mammal Protection Act Incidental Harassment Authorizations. We found PSO data collection fields and monitoring reports need standardization requirements. Our evaluation of PSO data revealed that publicly available PSO data are limited. We recommend making PSO data publicly available. If these recommendations are adopted, PSO data could help to fill knowledge gaps about marine mammal distribution.

CancerX Data Sprint: Advancing national oncology data standards through a unique public-private partnership.

e23283 Background: In a concerted effort to enhance the quality, accessibility, and effectiveness of comprehensive real-world cancer datasets, CancerX, a public-private partnership announced by the White House recently conducted a demonstration project, the CancerX Data Sprint. CancerX Data Sprint attempted a novel approach to quickly inform collective efforts of the Center for Medicare and Medicaid Innovation (CMMI), the National Cancer Institute (NCI), the US Food and Drug Administration (FDA), and the Office of the National Coordinator for Health Information Technology (ONC) to advance cancer-related data standards. Specifically, at the intersection of CMMI’s Enhancing Oncology Model (EOM) and the development of ONC’s United States Core Data for Interoperability (USCDI+) – Oncology extension, CancerX leveraged its unique model and broad membership to report novel insights to advance data-driven innovations in oncology research, care, and policy. Methods: From Sept to Dec 2023, the Data Sprint convened 150+ member organizations from industry and government partners to 1) Identify the high-value research questions that could be asked about the standardized real-world data (RWD) generated through EOM 2) Supplement the existing data elements with new ones to extend and enhance the ability to conduct scientific, clinical, and research inquiries with comprehensive datasets. The CancerX community opined via surveys, written feedback, and live workshops to identify key data elements, discuss their clinical value and technical feasibility, and consider their use in real-world settings as part of the comprehensive datasets. Results: Building on the current EOM clinical data elements, we identified and reported 15 new clinical data elements for considerations with high clinical utility and ease of technical abstraction. This comprehensive RWD encompasses a diverse range of patient demographics, clinical details, treatment histories, and outcomes, creating a more accurate and inclusive portrayal of cancer treatment effectiveness and patient journeys. This depth of information is crucial for optimizing the personalization of treatment pathways, conducting impact assessments, and addressing healthcare disparities. Essentially, the new datasets serve as a valuable repository of insights, driving advancements in cancer research, treatment and elevating care quality. Conclusions: CancerX remains committed to supporting federal data initiatives like USCDI+ Cancer standards development and others by providing recommendations for essential data elements implementation to enhance clinical utility, technical feasibility, and exchange of standardized cancer data. By adopting a unique approach and assembling an interdisciplinary group, we can ensure that data standardization efforts prioritize high-utility data elements, ultimately maximizing benefits for our patients.

Implementation and Execution of Big Data-based Studies in Ophthalmology within the Framework of the GDPR.

The processing of the retrospective data pool for ophthalmology holds huge potential, especially for the research sector. "Big Data" enables medical science to draw conclusions for the future from historical data. Based on the evaluation of such data, algorithms could be trained, for instance, that are capable of making decisions with the help of artificial intelligence. As a result, the medical decision-making process on certain issues could be accelerated, enriched in qualitative and quantitative terms, or even completely be taken over. Ophthalmology is a rapidly evolving field. Due to the multitude of partly automated medical imaging technologies and the predestined accessibility of the eye for such technologies, ophthalmology, similarly to radiology or dermatology, is well suited for artificial intelligence-assisted image data analysis and the frequently associated initiation of diagnosis and therapy. Meanwhile, numerous studies exist based on AI-assisted image data analysis of ophthalmological image data. To the extent that the algorithms filter out results from the data pools by means of calculation rules and are even capable of making independent decisions on the basis of decision trees, the enormous benefit and, simultaneously, the profit for scientific research is quite obvious. Accordingly, it would be desirable to have unrestricted and comprehensive possibility of corresponding data processing of these health data for ophthalmological research. In spite of the potential for ophthalmology, for which there is only fragmentary evidence, the question of practical feasibility arises. In particular, the legal requirements and limits of European and national data protection law must be taken into account, prior to any unreflected processing of personal (health) data. Only by doing so can we circumvent existing obstacles and pitfalls, which can lead to severe fines. Most important are to date the requirements of two legal texts: The General Data Protection Regulation (GDPR) and the Federal Data Protection Act (BDSG). This article provides an overview of the relevant legal requirements applicable in the field of ophthalmology and highlights the major pitfalls and implementation requirements.

Transforming Indigenous Procurement: Empowerment, Challenges, and the Road Ahead

The path toward economic reconciliation between Indigenous and non-Indigenous populations in Canada is a complex and vital journey that requires careful consideration of historical injustices and contemporary challenges. This paper focuses on the role of public procurement in addressing economic disparities and strengthening the nation-to-nation relationship between the Government of Canada and Indigenous communities. It provides an overview of public procurement's strategic importance, analyzes Indigenous federal procurement data from 2009 to May 2023 to identify trends and areas for improvement, and presents insights from a 2023 Indigenous procurement survey. Key findings emphasize the need to align Indigenous business capacities with procurement activities, promote inclusivity, and establish effective communication and mentorship programs. Implementing these recommendations can advance economic reconciliation and promote fairness within Canadian society.

NNI nanoinformatics conference 2023: Movement toward a common infrastructure for federal nanoEHS data computational toxicology: Short communication

The National Nanotechnology Initiative organized a Nanoinformatics Conference in the 2023 Biden-Harris Administration’s Year of Open Science, which included interested U.S. and EU stakeholders, and preceded the U.S.-EU COR meeting on November 15th, 2023 in Washington, D.C. Progress in the development of a common nanoinformatics infrastructure in the European Union and United States were discussed. Development of contributing, individual database projects, and their strengths and weaknesses, were highlighted. Recommendations and next steps for a U.S. nanoEHS common infrastructure were discussed in light of the pending update of the National Nanotechnology Initiative (NNI)’s Environmental, Health and Safety Research Strategy, and U.S. efforts to curate and house nano Environmental Health and Safety (nanoEHS) data from U.S. federal stakeholder groups. Improved data standards, for reporting and storage have been identified as areas where concerted efforts could most benefit initially. Areas that were not addressed at the conference, but that are critical to progress of the U.S. federal consortium effort are the evaluation of data formats according to use and sustainability measures; modeler and end user, including risk-assessor and regulator perspectives; a need for a community forum or shared data location that is not hosted by any individual U.S. federal agency, and is accessible to the public; as well as emerging needs for integration with new data types such as micro and nano plastics, and interoperability with other data and meta-data, such as adverse outcome pathway information. Future progress will depend on continued interaction of the U.S. and EU CORs, stakeholders and partners in the continued development goals for shared or interoperable infrastructure for nanoEHS.

Indian Preference and the status of American Indians and Alaska Natives in the federal service: Employment, earnings, authority, and perceptions of fairness

AbstractPublic administration scholars have largely ignored American Indians and Alaska Natives in their studies of racial disparities in the federal service, despite strong reasons to believe they face discrimination. Using three large federal data sets (the American Community Survey, federal personnel records, and the Federal Employee Viewpoint Survey), we compare the status of American Indians and Alaska Natives in the federal service to both Whites and other minorities. We find that, largely due to Indian Preference, American Indians and Alaska Natives are much more likely than Blacks, Whites, Latinos, and Asians to hold federal jobs, but they are highly concentrated in the Bureau of Indian Affairs and the Indian Health Service, agencies with which they have a sordid and fraught history. This concentration allows them to work in positions that may advance the interests of their communities and increases their probabilities of being supervisors, but it does not prevent them from being among the poorest‐paid and least‐satisfied employees in the federal service.