Invasive species - American bullfrog (Lithobates catesbeianus) in Flanders, Belgium is a species occurrence dataset published by the Research Institute for Nature and Forest (INBO). The dataset contains over 7,500 occurrences (25% of which are American bullfrogs) sampled between 2010 until now, in the months April to October. The data are compiled from different sources at the INBO, but most of the occurrences were collected through fieldwork for the EU co-funded Interreg project INVEXO (http://www.invexo.eu). In this project, research was conducted on different methods for the management of American bullfrog populations, an alien invasive species in Belgium. Captured bullfrogs were almost always removed from the environment and humanely killed, while the other occurrences are recorded bycatch, which were released upon catch (see bibliography for detailed descriptions of the methods). Therefore, caution is advised when using these data for trend analysis, distribution range calculation, or other. Issues with the dataset can be reported at https://github.com/inbo/data-publication/tree/master/datasets/invasive-bullfrog-occurrences

We strongly believe an open attitude is essential for tackling the IAS problem (Groom et al. 2015). To allow anyone to use this dataset, we have released the data to the public domain under a Creative Commons Zero waiver (http://creativecommons.org/publicdomain/zero/1.0/). We would appreciate it however if you read and follow these norms for data use (http://www.inbo.be/en/norms-for-data-use) and provide a link to the original dataset (https://doi.org/10.15468/2hqkqn) whenever possible. If you use these data for a scientific paper, please cite the dataset following the applicable citation norms and/or consider us for co-authorship. We are always interested to know how you have used or visualized the data, or to provide more information, so please contact us via the contact information provided in the metadata, opendata@inbo.be or https://twitter.com/LifeWatchINBO.

Changelog:

Update September 20, 2021: Data and overview updated to reflect data used in the September 15 story Over Half of States Have Rolled Back Public Health Powers in Pandemic. It includes 303 state or local public health leaders who resigned, retired or were fired between April 1, 2020 and Sept. 12, 2021. Previous versions of this dataset reflected data used in the Dec. 2020 and April 2021 stories.

Overview

Across the U.S., state and local public health officials have found themselves at the center of a political storm as they combat the worst pandemic in a century. Amid a fractured federal response, the usually invisible army of workers charged with preventing the spread of infectious disease has become a public punching bag.

In the midst of the coronavirus pandemic, at least 303 state or local public health leaders in 41 states have resigned, retired or been fired since April 1, 2020, according to an ongoing investigation by The Associated Press and KHN.

According to experts, that is the largest exodus of public health leaders in American history.

Many left due to political blowback or pandemic pressure, as they became the target of groups that have coalesced around a common goal — fighting and even threatening officials over mask orders and well-established public health activities like quarantines and contact tracing. Some left to take higher profile positions, or due to health concerns. Others were fired for poor performance. Dozens retired. An untold number of lower level staffers have also left.

The result is a further erosion of the nation’s already fragile public health infrastructure, which KHN and the AP documented beginning in 2020 in the Underfunded and Under Threat project.

Findings

The AP and KHN found that:

• One in five Americans live in a community that has lost its local public health department leader during the pandemic
• Top public health officials in 28 states have left state-level departments ## Using this data To filter for data specific to your state, use this query

To get total numbers of exits by state, broken down by state and local departments, use this query

Methodology

KHN and AP counted how many state and local public health leaders have left their jobs between April 1, 2020 and Sept. 12, 2021.

The government tasks public health workers with improving the health of the general population, through their work to encourage healthy living and prevent infectious disease. To that end, public health officials do everything from inspecting water and food safety to testing the nation’s babies for metabolic diseases and contact tracing cases of syphilis.

Many parts of the country have a health officer and a health director/administrator by statute. The analysis counted both of those positions if they existed. For state-level departments, the count tracks people in the top and second-highest-ranking job.

The analysis includes exits of top department officials regardless of reason, because no matter the reason, each left a vacancy at the top of a health agency during the pandemic. Reasons for departures include political pressure, health concerns and poor performance. Others left to take higher profile positions or to retire. Some departments had multiple top officials exit over the course of the pandemic; each is included in the analysis.

Reporters compiled the exit list by reaching out to public health associations and experts in every state and interviewing hundreds of public health employees. They also received information from the National Association of City and County Health Officials, and combed news reports and records.

Public health departments can be found at multiple levels of government. Each state has a department that handles these tasks, but most states also have local departments that either operate under local or state control. The population served by each local health department is calculated using the U.S. Census Bureau 2019 Population Estimates based on each department’s jurisdiction.

KHN and the AP have worked since the spring on a series of stories documenting the funding, staffing and problems around public health. A previous data distribution detailed a decade's worth of cuts to state and local spending and staffing on public health. That data can be found here.

Attribution

Findings and the data should be cited as: "According to a KHN and Associated Press report."

Is Data Missing?

If you know of a public health official in your state or area who has left that position between April 1, 2020 and Sept. 12, 2021 and isn't currently in our dataset, please contact authors Anna Maria Barry-Jester annab@kff.org, Hannah Recht hrecht@kff.org, Michelle Smith mrsmith@ap.org and Lauren Weber laurenw@kff.org.

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Public opinion poll on: Animals; Asia; Business; China; Communications Technology; Congress; Consumer; Economics; Elections; Energy; Environment; Europe; Family; Finances; Foreign Policy; Future; Government; Groups and Organizations; Health; Ideology; India; Information; Japan; Latin America; Local; Media; Mood; Notable People; Nuclear; Participation; Political Partisanship; Presidency; Regulation; Religion; Science; Social Media; Spending; States; Taxing; Technology; Television; Transportation.

The data consist of transcripts of interviews with 19 individuals from Brazil and 5 individuals from Colombia, who are all involved in Black and Indigenous activist organisations or in state agencies that are charged with promoting anti-racism and/or human rights. Each transcript begins with a paragraph giving contextual informationLatin America has often been held up as a region where racism is less of a problem than in regions such as the United States or Europe. Because most people are 'mestizos' (mixed race) and mixture is often seen as the essence of national identity, clear racial boundaries are blurred, resulting in comparatively low levels of racial segregation and a traditionally low public profile for issues of race. In Europe and the United States, the racial mixture and interaction across racial boundaries, which are typical of Latin America and are becoming more visible elsewhere, are heralded by some observers as leading towards a 'post-racial' reality, where anti-racism and multiculturalism - seen in this view as divisive policies that accentuate social differences - become unnecessary. Critics point out that mixture is not an antidote to racial inequality and racism in Latin America: they all coexist. This severely qualifies claims that mixture can lead to a 'post-racial' era. This project will investigate anti-racist practices and ideologies in Bolivia, Brazil, Colombia and Mexico. The project will contribute to conceptualising and addressing problems of racism, racial inequality and anti-racism in the region. We also propose that Latin America presents new opportunities for thinking about racism and anti-racism in a 'post-racial' world. Understanding how racism and anti-racism are conceived and practised in Latin America - in contexts in which mixture is pervasive - can help us to understand how to think about racism and anti-racism in other regions of the world, where notions of race have been changing in some respects towards Latin American patterns. It is also crucial to show the variety of ways in which mixture operates and co-exists with racism in Latin America - a region that is far from homogeneous. Research teams in each country, working with a range of organisations concerned with racism and discrimination, will explore how the organisations conceptualise and address key problems, which are becoming more salient in other regions, which confront similar scenarios. First, how to practice anti-racism when most people are mixed and when they may deny the importance of race and racism and themselves be both victims and the perpetrators of racism. Second, how to conceptualise and practice anti-racism when 'culture' seems to be the dominant discourse for talking about difference, but when physical difference (skin colour, hair type, etc.) remain powerful but often unacknowledged signs that move people to discriminate. Third, how to understand racism and combat it when race and class coincide to a great extent and make it easy to deny that race and racism are important factors. Fourth, how to make sure anti-racism addresses gender difference effectively, in a context in which mixture between white men and non-white women has been seen as the founding act of the nation. Fifth, how to pursue anti-racism when it is often claimed that there is little overt racist violence and that this is evidence of racial tolerance. We will explore how these elements structure - and may constrain - ideas about (anti-)racism within institutions, organisations and everyday practice. Our project will work with organisations in Bolivia, Brazil, Colombia and Mexico - countries that capture a good range of the region's diversity - to explore how racism and anti-racism are conceptualised and addressed in state and non-state circles, in legislation and the media, and in a variety of campaigns and projects. We aim to strengthen anti-racist practice in Latin America by feeding back our findings and by helping build networks; and to provide useful insights for understanding racism and anti-racism within and outside the region. The project carried out research in four countries, Brazil, Colombia, Ecuador and Mexico. We started by scoping out a broad range of organizations and individuals who were working in a direct or indirect fashion to challenge racism and racial inequality. We then selected seventeen case studies (over a third of which were Indigenous), with which we worked in depth, while also touching on about twenty other cases in a less intensive way. The cases were selected in order to include both Black and Indigenous organisations and cases, and to include a range of cases from government bodies to grassroots activist movements, plus some legal processes in which a variety of actors and organizations were involved. Our methods were mainly ethnography and interviews, undertaken principally by the four postdoctoral researchers, each of whom worked in one country. Some interviews were done with the assistance of a research assistant hired in the country. The interviews were conducted mostly in 2017, with some in 2018, in localities appropriate to the case study, such as an organization’s offices, an individual’s residence, or an agreed neutral location (e.g. a café, a village square, a classroom). Some interviews were informal conservations, but most were at least semi-structured. Common interview guides were not used, as each interview was specific to the case in question. Many interviews were audio-recorded (some were video-recorded) and selected interviews were transcribed in full or in part. Files with the original audio recordings and the transcripts are stored on a secure server in the University of Manchester. The files uploaded here are a selection of the transcribed interviews.

Analysis of ‘US Public Food Assistance’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/jpmiller/publicassistance on 13 February 2022.

--- Dataset description provided by original source is as follows ---

Context

This dataset focuses on public assistance programs in the United States that provide food, namely SNAP and WIC. If you are interested in a broader picture of food security across the world, please see Food Security Indicators for the World 2016-2020.

Initial coverage was for the Special Supplemental Nutrition Program for Women, Infants, and Children Program, or simply WIC. The program allocates Federal and State funds to help low-income women and children up to age five who are at nutritional risk. Funds are used to provide supplemental foods, baby formula, health care, and nutrition education.

Starting with version 5, the dataset also covers the US Supplemental Nutrition Assistance Program, more commonly known as SNAP. The program is the successor to the Food Stamps program previously in place. The program provides food assistance to low-income families in the form of a debit card. A 2016 study using POS data from SNAP-eligible vendors showed the three most purchased types of food to be meats, sweetened beverages, and vegetables.

Content

Files may include participation data and spending for state programs, and poverty data for each state. Data for WIC covers fiscal years 2013-2016, which is actually October 2012 through September 2016. Data for SNAP covers 2015 to 2020.

Motivation

My original purpose here is two-fold:

• Explore various aspects of US Public Assistance. Show trends over recent years and better understand differences across state agencies. Although the federal government sponsors the program and provides funding, program are administered at the state level and can widely vary. Indian nations (native Americans) also administer their own programs.

• Share with the Kaggle Community the joy - and pain - of working with government data. Data is often spread across numerous agency sites and comes in a variety of formats. Often the data is provided in Excel, with the files consisting of multiple tabs. Also, files are formatted as reports and contain aggregated data (sums, averages, etc.) along with base data.

As of March 2nd, I am expanding the purpose to support the M5 Forecasting Challenges here on Kaggle. Store sales are partly driven by participation in Public Assistance programs. Participants typically receive the items free of charge. The store then recovers the sale price from the state agencies administering the program.

Additional Content Ideas

The dataset can benefit greatly from additional content. Economics, additional demographics, administrative costs and more. I'd like to eventually explore the money trail from taxes and corporate subsidies, through the government agencies, and on to program participants. All community ideas are welcome!

--- Original source retains full ownership of the source dataset ---

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Topics of interest include: the 30 hour work week; the Academy awards; awareness towards Australia; broadcasting regulation; the Canadian Broadcasting Corporation (CBC); dining out; doctors; federal elections; a two party electoral system; funerals; government competition; health care; hospital problems; husbands' faults; marriage; movies; phone ownership; preferred political parties; price trends; the Quebec provincial election; television's influence; the Trans-Canada pipeline; union membership; voting behaviour; and wives faults. Basic demographics variables are also included. 248 - May This Gallup polls seeks the opinions of Canadians on current events in Canada and around the world, the continuing development of industry and communities in Canada, and some lighter topics including holidays. Respondents were also asked questions so that they could be grouped according to geographic, demographic, and social variables. 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This dataset was created to support the 2016 DIA (Related publication only available in Spanish). The accelerated aging process that countries in Latin America and the Caribbean are undergoing imposes unprecedented pressures on the long-term care sector. In this context, the growing demand for care from the elderly population occurs alongside a reduction in the availability of informal care. Governments in the region must prepare to address these pressures by supporting the provision of care services to alleviate social exclusion in old age. The Inter-American Development Bank has created an Observatory on Aging and Care — the focus of this policy brief — aimed at providing decision-makers with information to design policies based on available empirical evidence. In this initial phase, the Observatory seeks to document the demographic situation of countries in the region, the health of their elderly population, their limitations and dependency status, as well as their main socioeconomic characteristics. The goal is to estimate the care needs countries in the region will face. This brief summarizes the key findings from an initial analysis of the data. The results highlight the scale of the problem. The figures speak for themselves: in the region, 11% of the population aged 60 and older is dependent. Both the magnitude and intensity of dependency increase with age. Women are the most affected across all age groups. This policy brief is part of a series of studies on dependency care, including works by Caruso, Galiani, and Ibarrarán (2017); Medellín et al. (2018); López-Ortega (2018); and Aranco and Sorio (2018).

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The American Samoa Local Action Strategies (LAS) are the result of a nearly two-year process that saw input from territorial agencies, non-profit groups, interested individuals, and other stake-holders such as local fishers, and federal agency partners. This process was initiated through the American Samoa Coral Reef Advisory Group (CRAG), a voluntary committee comprised of numerous agencies and academic institutions in the territory concerned with coral reef issues. Since its inception in 1998, CRAG has overseen many successful management and science activities, has increased member-agency collaboration and has improved alignment and cooperation with non-CRAG agencies that have common interests. To address LAS focus areas, CRAG developed both short- and long-term action plans that prioritize activities for funding. Where possible, current and ongoing activities were incorporated into each LAS to provide continuity and networking, and to underscore that individual agency mandates and projects are supported by the CRAG as a whole. Each LAS consists of goals, success indicators, projects and timelines, and will continue to evolve and develop as new resources are brought to bear, and as projects are completed. Available online Call Number: [EL] Physical Description: 2 Pages

This table contains data on the percent of households paying more than 30% (or 50%) of monthly household income towards housing costs for California, its regions, counties, cities/towns, and census tracts. Data is from the U.S. Department of Housing and Urban Development (HUD), Consolidated Planning Comprehensive Housing Affordability Strategy (CHAS) and the U.S. Census Bureau, American Community Survey (ACS). The table is part of a series of indicators in the [Healthy Communities Data and Indicators Project of the Office of Health Equity] Affordable, quality housing is central to health, conferring protection from the environment and supporting family life. Housing costs—typically the largest, single expense in a family's budget—also impact decisions that affect health. As housing consumes larger proportions of household income, families have less income for nutrition, health care, transportation, education, etc. Severe cost burdens may induce poverty—which is associated with developmental and behavioral problems in children and accelerated cognitive and physical decline in adults. Low-income families and minority communities are disproportionately affected by the lack of affordable, quality housing. More information about the data table and a data dictionary can be found in the Attachments.

Social vulnerability is defined as the disproportionate susceptibility of some social groups to the impacts of hazards, including death, injury, loss, or disruption of livelihood. In this dataset from Climate Ready Boston, groups identified as being more vulnerable are older adults, children, people of color, people with limited English proficiency, people with low or no incomes, people with disabilities, and people with medical illnesses. Source:The analysis and definitions used in Climate Ready Boston (2016) are based on "A framework to understand the relationship between social factors that reduce resilience in cities: Application to the City of Boston." Published 2015 in the International Journal of Disaster Risk Reduction by Atyia Martin, Northeastern University.Population Definitions:Older Adults:Older adults (those over age 65) have physical vulnerabilities in a climate event; they suffer from higher rates of medical illness than the rest of the population and can have some functional limitations in an evacuation scenario, as well as when preparing for and recovering from a disaster. Furthermore, older adults are physically more vulnerable to the impacts of extreme heat. Beyond the physical risk, older adults are more likely to be socially isolated. Without an appropriate support network, an initially small risk could be exacerbated if an older adult is not able to get help.Data source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract for population over 65 years of age.Attribute label: OlderAdultChildren: Families with children require additional resources in a climate event. When school is cancelled, parents need alternative childcare options, which can mean missing work. Children are especially vulnerable to extreme heat and stress following a natural disaster.Data source: 2010 American Community Survey 5-year Estimates (ACS) data by census tract for population under 5 years of age.Attribute label: TotChildPeople of Color: People of color make up a majority (53 percent) of Boston’s population. People of color are more likely to fall into multiple vulnerable groups aswell. People of color statistically have lower levels of income and higher levels of poverty than the population at large. People of color, many of whom also have limited English proficiency, may not have ready access in their primary language to information about the dangers of extreme heat or about cooling center resources. This risk to extreme heat can be compounded by the fact that people of color often live in more densely populated urban areas that are at higher risk for heat exposure due to the urban heat island effect.Data source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract: Black, Native American, Asian, Island, Other, Multi, Non-white Hispanics.Attribute label: POC2Limited English Proficiency: Without adequate English skills, residents can miss crucial information on how to preparefor hazards. Cultural practices for information sharing, for example, may focus on word-of-mouth communication. In a flood event, residents can also face challenges communicating with emergency response personnel. If residents are more sociallyisolated, they may be less likely to hear about upcoming events. Finally, immigrants, especially ones who are undocumented, may be reluctant to use government services out of fear of deportation or general distrust of the government or emergency personnel.Data Source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract, defined as speaks English only or speaks English “very well”.Attribute label: LEPLow to no Income: A lack of financial resources impacts a household’s ability to prepare for a disaster event and to support friends and neighborhoods. For example, residents without televisions, computers, or data-driven mobile phones may face challenges getting news about hazards or recovery resources. Renters may have trouble finding and paying deposits for replacement housing if their residence is impacted by flooding. Homeowners may be less able to afford insurance that will cover flood damage. Having low or no income can create difficulty evacuating in a disaster event because of a higher reliance on public transportation. If unable to evacuate, residents may be more at risk without supplies to stay in their homes for an extended period of time. Low- and no-income residents can also be more vulnerable to hot weather if running air conditioning or fans puts utility costs out of reach.Data source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract for low-to- no income populations. The data represents a calculated field that combines people who were 100% below the poverty level and those who were 100–149% of the poverty level.Attribute label: Low_to_NoPeople with Disabilities: People with disabilities are among the most vulnerable in an emergency; they sustain disproportionate rates of illness, injury, and death in disaster events.46 People with disabilities can find it difficult to adequately prepare for a disaster event, including moving to a safer place. They are more likely to be left behind or abandoned during evacuations. Rescue and relief resources—like emergency transportation or shelters, for example— may not be universally accessible. Research has revealed a historic pattern of discrimination against people with disabilities in times of resource scarcity, like after a major storm and flood.Data source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract for total civilian non-institutionalized population, including: hearing difficulty, vision difficulty, cognitive difficulty, ambulatory difficulty, self-care difficulty, and independent living difficulty. Attribute label: TotDisMedical Illness: Symptoms of existing medical illnesses are often exacerbated by hot temperatures. For example, heat can trigger asthma attacks or increase already high blood pressure due to the stress of high temperatures put on the body. Climate events can interrupt access to normal sources of healthcare and even life-sustaining medication. Special planning is required for people experiencing medical illness. For example, people dependent on dialysis will have different evacuation and care needs than other Boston residents in a climate event.Data source: Medical illness is a proxy measure which is based on EASI data accessed through Simply Map. Health data at the local level in Massachusetts is not available beyond zip codes. EASI modeled the health statistics for the U.S. population based upon age, sex, and race probabilities using U.S. Census Bureau data. The probabilities are modeled against the census and current year and five year forecasts. Medical illness is the sum of asthma in children, asthma in adults, heart disease, emphysema, bronchitis, cancer, diabetes, kidney disease, and liver disease. A limitation is that these numbers may be over-counted as the result of people potentially having more than one medical illness. Therefore, the analysis may have greater numbers of people with medical illness within census tracts than actually present. Overall, the analysis was based on the relationship between social factors.Attribute label: MedIllnesOther attribute definitions:GEOID10: Geographic identifier: State Code (25), Country Code (025), 2010 Census TractAREA_SQFT: Tract area (in square feet)AREA_ACRES: Tract area (in acres)POP100_RE: Tract population countHU100_RE: Tract housing unit countName: Boston Neighborhood

This statistic shows a ranking of the estimated per capita consumer spending on healthcare in 2020 in Latin America and the Caribbean, differentiated by country. Consumer spending here refers to the domestic demand of private households and non-profit institutions serving households (NPISHs) in the selected region. Spending by corporations or the state is not included. Consumer spending is the biggest component of the gross domestic product as computed on an expenditure basis in the context of national accounts. The other components in this approach are consumption expenditure of the state, gross domestic investment as well as the net exports of goods and services. Consumer spending is broken down according to the United Nations' Classification of Individual Consumption By Purpose (COICOP). The shown data adheres broadly to group 06. As not all countries and regions report data in a harmonized way, all data shown here has been processed by Statista to allow the greatest level of comparability possible. The underlying input data are usually household budget surveys conducted by government agencies that track spending of selected households over a given period.The data is shown in nominal terms which means that monetary data is valued at prices of the respective year and has not been adjusted for inflation. For future years the price level has been projected as well. The data has been converted from local currencies to US$ using the average exchange rate of the respective year. For forecast years, the exchange rate has been projected as well. The timelines therefore incorporate currency effects.The shown forecast is adjusted for the expected impact of the COVID-19 pandemic on the local economy. The impact has been estimated by considering both direct (e.g. because of restrictions on personal movement) and indirect (e.g. because of weakened purchasing power) effects. The impact assessment is subject to periodic review as more data becomes available.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in more than 150 countries and regions worldwide. All input data are sourced from international institutions, national statistical offices, and trade associations. All data has been are processed to generate comparable datasets (see supplementary notes under details for more information).

About this dataset

Context

The dataset tabulates the population of Mentone by race. It includes the population of Mentone across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Mentone across relevant racial categories.

Key observations

The percent distribution of Mentone population by race (across all racial categories recognized by the U.S. Census Bureau): 95.28% are white, 0.56% are American Indian and Alaska Native and 4.17% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the Mentone
• Population: The population of the racial category (excluding ethnicity) in the Mentone is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Mentone total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Mentone Population by Race & Ethnicity. You can refer the same here

This dataset provides a survey of Irish writers publishing in The New Yorker magazine from 1940 to 1980. Methodology I conduct the survey through archival research and secondary references. The primary sources are The New Yorker's digital archive and the New Yorker Records housed in the New York Public Library. Parameters The timeframe of the survey concerns The New Yorker’s international expansion in the middle decades of the twentieth century. It starts from 1940 and ends in 1980, when the magazine industry’s cultural impact was eclipsed by the popularity of TV. For the purpose of the project, I focus on "fiction" contributions. Verse and shorter writings (such as column pieces and book reviews) are not included. Therefore, Maeve Brennan's shorter pieces under her alias "the long-winded lady" and Patricia Collinge's shorter contributions are not included in the quantatative survey. This survey includes both Irish and Irish-American writers. One key criterium of the selection is the writer’s connection with Ireland and Irish culture. Irish-American writers whose works are more concerned about (Irish-)America rather than Ireland itself are excluded from the survey. Therefore, Elizabeth Cullinan and J.P. Donleavy are included, while John O’Hara and Mary McCarthy are not. Notes for Users The list is presented in the chronological order of the contributions’ appearance in the magazine. The date format follows the international convention (ISO8601), thus: year/month/day. The date refers to the publication of The New Yorker issues. The New Yorker is a weekly, and the timeframe of the project spans four decades. This means that there are thousands of back issues under examination. I acknowledge the possibility that there are Irish writers whose contributions in the magazine escaped my attention. If there is any omission, I would appreciate the user’s input to update the survey. It is hoped that this survey will help researchers investigate the Irish connections with one of America’s most influential publications. Teachers, students, and the general public may also use this list as a guide to better appreciate these fascinating Irish stories.

Consumer Confidence in the United States increased to 61.80 points in July from 60.70 points in June of 2025. This dataset provides the latest reported value for - United States Consumer Sentiment - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This statistic shows a ranking of the estimated current healthcare spending per capita in 2020 in Latin America and the Caribbean, differentiated by country. The spending refers to the average current spending of both governments and consumers per inhabitant.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in more than 150 countries and regions worldwide. All input data are sourced from international institutions, national statistical offices, and trade associations. All data has been are processed to generate comparable datasets (see supplementary notes under details for more information).

The Bureau of the Census has released Census 2000 Summary File 1 (SF1) 100-Percent data. The file includes the following population items: sex, age, race, Hispanic or Latino origin, household relationship, and household and family characteristics. Housing items include occupancy status and tenure (whether the unit is owner or renter occupied). SF1 does not include information on incomes, poverty status, overcrowded housing or age of housing. These topics will be covered in Summary File 3. Data are available for states, counties, county subdivisions, places, census tracts, block groups, and, where applicable, American Indian and Alaskan Native Areas and Hawaiian Home Lands. The SF1 data are available on the Bureau's web site and may be retrieved from American FactFinder as tables, lists, or maps. Users may also download a set of compressed ASCII files for each state via the Bureau's FTP server. There are over 8000 data items available for each geographic area. The full listing of these data items is available here as a downloadable compressed data base file named TABLES.ZIP. The uncompressed is in FoxPro data base file (dbf) format and may be imported to ACCESS, EXCEL, and other software formats. While all of this information is useful, the Office of Community Planning and Development has downloaded selected information for all states and areas and is making this information available on the CPD web pages. The tables and data items selected are those items used in the CDBG and HOME allocation formulas plus topics most pertinent to the Comprehensive Housing Affordability Strategy (CHAS), the Consolidated Plan, and similar overall economic and community development plans. The information is contained in five compressed (zipped) dbf tables for each state. When uncompressed the tables are ready for use with FoxPro and they can be imported into ACCESS, EXCEL, and other spreadsheet, GIS and database software. The data are at the block group summary level. The first two characters of the file name are the state abbreviation. The next two letters are BG for block group. Each record is labeled with the code and name of the city and county in which it is located so that the data can be summarized to higher-level geography. The last part of the file name describes the contents . The GEO file contains standard Census Bureau geographic identifiers for each block group, such as the metropolitan area code and congressional district code. The only data included in this table is total population and total housing units. POP1 and POP2 contain selected population variables and selected housing items are in the HU file. The MA05 table data is only for use by State CDBG grantees for the reporting of the racial composition of beneficiaries of Area Benefit activities. The complete package for a state consists of the dictionary file named TABLES, and the five data files for the state. The logical record number (LOGRECNO) links the records across tables.

This statistic shows a ranking of the estimated current healthcare spending in 2020 in Latin America and the Caribbean, differentiated by country. The spending refers to current spending of both governments and consumers.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in more than 150 countries and regions worldwide. All input data are sourced from international institutions, national statistical offices, and trade associations. All data has been are processed to generate comparable datasets (see supplementary notes under details for more information).