This transformed view of Employee Demographics - Public dataset counts the number of and percentage of city employees by race as self-reported by employee based on EEOC classification. This information is used by "City Employee vs. Community Demographics dataset" at https://citydata.mesaaz.gov/Economic-Development/Chart-Data-for-City-Employee-vs-Community-Demograp/bt2n-zimw

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The COVID-19 pandemic has significantly affected the global workforce, presenting unprecedented challenges to managers and practitioners of strategic human resource management. Pandemic-influenced changes in the employment relationship highlighting the need for adaptation in order to facilitate a return to pre-pandemic conditions. Crises such as this can have a detrimental effect on employees’ psychological contract, which in turn can hinder the organization’s ability to thrive in the post-COVID-19 era and impede the development of high commitment levels in the aftermath of the crisis. Emotional intelligence plays an increasingly vital role in effectively navigating the crisis and providing support to employees, while also facilitating the reconstruction of the psychological contract. Therefore, this study aims to explain the role of emotional intelligence of strategic human resource management practitioners on affective organizational commitment and the possible mediating effect of the psychological contract in that relationship. A quantitative study took place in February 2023 among 286 HR directors, HR managers, and HR officers in higher education institutions in Georgia. Partial Least Squares for Structural Equation Modelling was applied for data analysis. The results revealed that the emotional intelligence of strategic human resource management practitioners has a positive impact on the psychological contract and the affective organizational commitment. This study supports the idea that emotional intelligence can transform strategic human resource management practitioners into individuals who engage in people-orientated activities. These activities aim to effectively acquire, utilize, and retain employees within an organization. The study also suggests that emotional intelligence can provide solutions to maintain high employee commitment during times of crisis and in the aftermath of unprecedented situations.

Some or all data, models, or code generated or used during the study are available in a repository or online in accordance with funder data retention policies.

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Demographic data for job applicants at the City of Gainesville for both General Government and GRU since October 2010.

Demographic data for job applicants at the City of Gainesville for both General Government and GRU since October 2010.

This report, prepared by the Country Operations Division of the Bank’s Southern Africa Department, presents the findings of two missions which visited Mozambique during April and September 1989. It discusses the evolution and continuing importance of the reform of the economic policy environment and has the additional objective of seeking to establish the significance of another key element of the Economic Rehabilitation Program (ERP), which was initiated in January 1987 and has since been consistently pursued by the Government of Mozambique. This element includes basic economic infrastructural support services and consequently, the report devotes considerable attention to identifying the means by which the infrastructure can be developed to facilitate and provide an incentive to both the productive and distributive sectors. The general objective of this report is to analyze the course of economic development over the first three years of the ERP, 1987-89, with a view to identifying the principal opportunities for future growth and to defining a more directed program for the medium term. The report has four major components: (a) the review and analysis of economic development under the ERP, 1986-89; (b) the analysis of the development constraints in three key areas of the economic infrastructure - transportation, financial, and marketing infrastructure; (c) the analysis of the development constraints in two key areas crucial to longer term development - issues of demographic and human resource development; and (d) the medium term policy and prospects for growth. This report includes tables.

The database comprises a spatially referenced compilation of the human development indexes. It includes 100 indicators of various human development spheres including demography, economics, finance, politics, equality, science and education, healthcare, culture, mobility and ecology. The statistics are attached to the authors' cartographic base with internationally recognised borders of 193 UN full members. The base allows to conduct complex spatial econometric analysis of social and political processes in the world using geoinformation systems. The database may be employed to analyse spatial differentiation of various aspects of human development.

Explore demographic data on the Massachusetts executive branch workforce. Track our progress toward our goals to reflect the diversity of the people we serve, and to stand out as an employer of choice.

Description

This comprehensive dataset provides a wealth of information about all countries worldwide, covering a wide range of indicators and attributes. It encompasses demographic statistics, economic indicators, environmental factors, healthcare metrics, education statistics, and much more. With every country represented, this dataset offers a complete global perspective on various aspects of nations, enabling in-depth analyses and cross-country comparisons.

Key Features

• Country: Name of the country.
• Density (P/Km2): Population density measured in persons per square kilometer.
• Abbreviation: Abbreviation or code representing the country.
• Agricultural Land (%): Percentage of land area used for agricultural purposes.
• Land Area (Km2): Total land area of the country in square kilometers.
• Armed Forces Size: Size of the armed forces in the country.
• Birth Rate: Number of births per 1,000 population per year.
• Calling Code: International calling code for the country.
• Capital/Major City: Name of the capital or major city.
• CO2 Emissions: Carbon dioxide emissions in tons.
• CPI: Consumer Price Index, a measure of inflation and purchasing power.
• CPI Change (%): Percentage change in the Consumer Price Index compared to the previous year.
• Currency_Code: Currency code used in the country.
• Fertility Rate: Average number of children born to a woman during her lifetime.
• Forested Area (%): Percentage of land area covered by forests.
• Gasoline_Price: Price of gasoline per liter in local currency.
• GDP: Gross Domestic Product, the total value of goods and services produced in the country.
• Gross Primary Education Enrollment (%): Gross enrollment ratio for primary education.
• Gross Tertiary Education Enrollment (%): Gross enrollment ratio for tertiary education.
• Infant Mortality: Number of deaths per 1,000 live births before reaching one year of age.
• Largest City: Name of the country's largest city.
• Life Expectancy: Average number of years a newborn is expected to live.
• Maternal Mortality Ratio: Number of maternal deaths per 100,000 live births.
• Minimum Wage: Minimum wage level in local currency.
• Official Language: Official language(s) spoken in the country.
• Out of Pocket Health Expenditure (%): Percentage of total health expenditure paid out-of-pocket by individuals.
• Physicians per Thousand: Number of physicians per thousand people.
• Population: Total population of the country.
• Population: Labor Force Participation (%): Percentage of the population that is part of the labor force.
• Tax Revenue (%): Tax revenue as a percentage of GDP.
• Total Tax Rate: Overall tax burden as a percentage of commercial profits.
• Unemployment Rate: Percentage of the labor force that is unemployed.
• Urban Population: Percentage of the population living in urban areas.
• Latitude: Latitude coordinate of the country's location.
• Longitude: Longitude coordinate of the country's location.

Potential Use Cases

• Analyze population density and land area to study spatial distribution patterns.
• Investigate the relationship between agricultural land and food security.
• Examine carbon dioxide emissions and their impact on climate change.
• Explore correlations between economic indicators such as GDP and various socio-economic factors.
• Investigate educational enrollment rates and their implications for human capital development.
• Analyze healthcare metrics such as infant mortality and life expectancy to assess overall well-being.
• Study labor market dynamics through indicators such as labor force participation and unemployment rates.
• Investigate the role of taxation and its impact on economic development.
• Explore urbanization trends and their social and environmental consequences.

The Global Demographic Data collection holds global gridded data products describing demographic information and water demand in relation to population data. Currently, water demand data are being distributed; population data will be added in the near future.

Country-level urban, rural and total population estimate data from World Resources Institute (WRI) for the years 1985, 1995, and 2025 were gridded by the University of New Hampshire's Water Systems Analysis Groupusing methods outlined in Vorosmarty et al. (2000) for use in estimating global water resources based on climate and population changes.

Currently available are five relative water demand (RWD) fraction data sets/ maps, produced by Vorosmarty et al. in their analysis of future water resources. The relative water demand is defined to be the total volume of water used either domestically, industrially or agriculturally (DIA) divided by the water discharge (Q). "Values of .2 to .4 indicate medium to high stress." (see Vorosmarty et al., 2000) This analysis deals only with sustainable water sources, and does not look at nonsustainable water sources, such a ground water mining. The RWD is computed on a .5 by .5 degree grid for two sentinel years: 1985 and 2025, which are two of the data sets. The ratio of the RWD for these two years provides a measure of change under scenarios of climate change only, population change only and the combination of climate change and population to produce the other three datasets. The ratio RWD values is relative to the RWD in the base year, 1985.

This dataset presents aggregated data regarding employee jobs and median employee income per job, classified by industry subdivision at Statistical Area Level 2 (SA2). The data spans over the 2014-15 financial year and is aggregated to the 2016 SA2 boundaries.

Jobs in Australia provide aggregate statistics and are sourced from the Linked Employer-Employee Dataset (LEED). It provides new information about filled jobs in Australia, the people who hold them, and their employers. An 'employee Job' refers to a job for which the occupant receives remuneration in wages, salary, payment in kind, or piece rates. This excludes self-employment jobs held by Owner-Managers of Unincorporated Enterprises (OMUE).

The job counts in this release differ from the filled job estimates from other sources such as the Australian Labour Account and the Labour Force Australia. The Jobs in Australia release provides insights into all jobs held throughout the year, while the Labour Account data provides the number of filled jobs at a point-in-time each quarter (and annually for the financial year reference period), and Labour Force Survey data measures the number of people employed each month.

For more information on the release please visit the Australian Bureau of Statistics

This release provides statistics on the number and nature of jobs, the people who hold them, and their employers. These statistics can be used to understand regional labour markets or to identify the impact of major changes in local communities. The release also provides new insights into the number of jobs people hold, the duration of jobs, and the industries and employment income of concurrent jobs.

The scope of these data includes individuals who submitted an individual tax return to the Australian Taxation Office (ATO), individuals who had a Pay As You Go (PAYG) payment summary issued by an employer and their employers.

AURIN has spatially enabled the original data. The following additional changes were made:

• Where data was not published for confidential reasons, "np" in the original data, the records have been set to null.

• Total values may be higher than the sum of the published components due to this confidentialisation.

Agricultural socialized service is gradually emerging as a new stimulus for enhancing the agricultural production environment. However, their precise impact on improving the agricultural ecological environment and promoting the green development of agriculture remains incompletely understood. Therefore, leveraging panel data spanning from 2003 to 2020 across 31 provinces in China, this study utilizes the bidirectional fixed effect model, moderating effect model, and spatial Durbin model to systematically assess the influence of agricultural socialized services on agricultural green development and its spatial ramifications. The findings show that (I) agricultural socialized services significantly contribute to promoting agricultural green development, particularly in regions with lower aging demographics. (II) The application of the spatial Durbin model reveals that this promotional effect does not exhibit significant spatial spillover effect. (III) The role of agricultural socialized services in fostering agricultural green development can be significantly enhanced by advancements in land transfer, agricultural technological innovations, and the improvement of rural human capital. In conclusion, the study provides a set of policy recommendations that include government financial support, facilitating land transfer, improving rural education and technical training, and promoting green production technologies to effectively promote agricultural green development.

This dataset offers a wealth of information about all countries worldwide, covering a broad range of indicators and attributes. It includes demographic statistics, economic indicators, environmental factors, healthcare metrics, education statistics, and much more. With every country represented, this dataset provides a complete global perspective on various aspects of nations, enabling in-depth analyses and cross-country comparisons.

Columns

• Country: Name of the country.
• Density (P/Km2): Population density measured in persons per square kilometre.
• Abbreviation: Abbreviation or code representing the country.
• Agricultural Land (%): Percentage of land area used for agricultural purposes.
• Land Area (Km2): Total land area of the country in square kilometres.
• Armed Forces Size: Size of the armed forces in the country.
• Birth Rate: Number of births per 1,000 population per year.
• Calling Code: International calling code for the country.
• Capital/Major City: Name of the capital or major city.
• CO2 Emissions: Carbon dioxide emissions in tonnes.
• CPI: Consumer Price Index, a measure of inflation and purchasing power.
• CPI Change (%): Percentage change in the Consumer Price Index compared to the previous year.
• Currency_Code: Currency code used in the country.
• Fertility Rate: Average number of children born to a woman during her lifetime.
• Forested Area (%): Percentage of land area covered by forests.
• Gasoline_Price: Price of gasoline per litre in USD.
• GDP: Gross Domestic Product, the total value of goods and services produced in the country.
• Gross Primary Education Enrollment (%): Gross enrolment ratio for primary education.
• Gross Tertiary Education Enrollment (%): Gross enrolment ratio for tertiary education.
• Infant Mortality: Number of deaths per 1,000 live births before reaching one year of age.
• Largest City: Name of the country's largest city.
• Life Expectancy: Average number of years a newborn is expected to live.
• Maternal Mortality Ratio: Number of maternal deaths per 100,000 live births.
• Minimum Wage: Minimum wage level in local currency.
• Official Language: Official language(s) spoken in the country.
• Out of Pocket Health Expenditure (%): Percentage of total health expenditure paid out-of-pocket by individuals.
• Physicians per Thousand: Number of physicians per thousand people.
• Population: Total population of the country.
• Population: Labour Force Participation (%): Percentage of the population that is part of the labour force.
• Tax Revenue (%): Tax revenue as a percentage of GDP.
• Total Tax Rate: Overall tax burden as a percentage of commercial profits.
• Unemployment Rate: Percentage of the labour force that is unemployed.
• Urban_population: Percentage of the population living in urban areas.
• Latitude: Latitude coordinate of the country's location.
• Longitude: Longitude coordinate of the country's location.

Distribution

The dataset is provided as a CSV file named world-data-2023.csv, with a size of 49.21 kB. It contains 35 columns and includes data for 195 unique countries, implying 195 records or rows.

Usage

Ideal applications and use cases for this dataset include: * Analysing population density and land area to study spatial distribution patterns. * Investigating the relationship between agricultural land and food security. * Examining carbon dioxide emissions and their impact on climate change. * Exploring correlations between economic indicators such as GDP and various socio-economic factors. * Investigating educational enrolment rates and their implications for human capital development. * Analysing healthcare metrics such as infant mortality and life expectancy to assess overall well-being. * Studying labour market dynamics through indicators such as labour force participation and unemployment rates. * Investigating the role of taxation and its impact on economic development. * Exploring urbanisation trends and their social and environmental consequences.

Coverage

This dataset offers a global geographic scope, covering all countries worldwide. The data pertains to the year 2023. It includes diverse demographic, economic, and social indicators, providing broad insights into various aspects of nations.

License

Attribution 4.0 International (CC BY 4.0)

Who Can Use It

This dataset is suitable for: * Data Analysts and Scientists: For statistical modelling, trend analysis, and pattern discovery. * Researchers and Academics: To support studies in economics, sociology, environmental science, and public health. * Policymakers and Government Agencies: For informing policy decisions and understanding global benchmarks. * Students: As a valuable resource for

This dataset presents aggregated data regarding the number of people employed in multiple jobs and their respective median income by the relevant statistical regions. The data spans over the 2012/13 financial year and is aggregated to the 2016 Greater Capital City Statistical Area (GCCSA) boundaries.

Jobs in Australia is a new release that provides aggregate statistics from the recently developed Linked Employer-Employee Dataset (LEED). It provides new information about filled jobs in Australia, the people who hold them, and their employers.

Jobs in Australia describes all job relationships accumulated over the course of a year. This means that job counts in this publication are higher than the estimates of filled jobs published in the quarterly Australian Labour Account, which provides a point-in-time, or stock measure. These statistics about jobs also differ from Labour Force Survey statistics, which estimate the number of people who held a job in each month.

This data is Australian Bureau of Statistics (ABS) data (catalogue number: 6160.0) used with permission from the ABS.

For more information on the release please visit the Australian Bureau of Statistics

The purpose of this publication is to provide new information about the number and nature of filled jobs in Australia, the people who hold them, and their employers. It includes information about multiple job-holding and employment in local areas. Jobs in Australia counts all jobs held during the reference year. This complements and expands on quarterly stock estimates of filled jobs presented in the Australian Labour Account.

AURIN has spatially enabled the original data. The following additional changes were made:

• Where data was not published for confidential reasons, "np" in the original data, the records have been set to null.

• Total values may be higher than the sum of the published components due to this confidentialisation.

The "Social, Economic, Environmental, Demographic Information System (SEEDIS)" is a research and development project at the Lawrence Berkeley Laboratory, supported by the U.S. Department of Energy (USDOE), U.S. Department of Labor (USDOL), and others. It was initiated in 1972 by USDOL as a demonstration project to link data from multiple sources. Since that time, the project has been expanded. SEEDIS's main purpose is to provide accurate, and timely information for policy formulation, implementation and management. The SEEDIS Project addresses these information needs by providing a unified framework for data management, information retrieval, statistical analysis, and graphic display of data from a collection of databases for various geographic levels and time periods, drawn from the U.S. Census Bureau, the U.S. Environmental Protection Agency (USEPA) and the Department of Health and Human Services.

SEEDIS contains information on Census, energy, environment, geography, health, population characteristics, and socioeconomic status. SEEDIS allows the user to produce graphical and map presentations of analyses of combinations of these data for a variety of geographic levels and scope.

SEEDIS' census information relates to population size by major racial and ethnic groupings for 1970 and 1980. These data are variously available at the national, state, county, city and census tract level.

SEEDIS' energy information relates to electrical generating capacity for 1960 through 1995. These data are available at the national, county, and standardized metropolitan statistical area (SMSA) level. The data system also contains 1970 residential housing data, and heating energy requirements in 1970, and biomass resources for 1976 and 2025 at the county geographic level.

SEEDIS' environmental information relates to air quality measurements for criteria pollutants. The data are available for 1974 through 1976 at the census tract level. They are derived from the AIRS data system (formerly SAROAD). Assessments include total suspended particulates (TSP), sulfur and nitrogen dioxides, photochemical oxidants, ozone, carbon monoxide, sulfates, and total and nonmethane hydrocarbons. For each pollutant, county estimates of pollutant concentration (at the position of the county population centroid) were calculated as the weighted geometric means of measurements from nearby stations, including stations in nearby counties. The location of the air quality monitoring stations is also available from the National Air Monitoring Stations (NAMS) data system.

SEEDIS' geographic information relates to the centroids of the 1970 household populations. The data are available for a variety of geographic levels. The areas, centroids, and boundaries of census tracts and counties are also included.

SEEDIS' health information relates to age-, sex-, and race-specific total mortality. The data are available for geographic levels as small as counties for the years 1969 through 1984. In addition, total annual leukemia mortality is available. Cancer incidence for 1973 through 1981 from the Surveillance, Epidemiologic, and End Results (SEER) registers is included for the states that participate in the program.

SEEDIS' population relates to age-, race-, and sex-specific population counts (from the 1980 Census) and estimates for the years 1950 to 1987. The data are available for varying geographic levels. Estimates are available from a variety of sources.

SEEDIS' economic information relates to labor force, employment by industry, income, education, fertility. It also contains data on the Census of Agriculture and many county- and state-specific data. LANGUAGE:

English ACCESS/AVAILABILITY:

Data Center: University of California at Berkeley (UCB) Dissemination Media: Hard copy (specialized data extraction service at cost), tape copies of selected data files File Format: Access Instructions: Contact the data center. Size: Memory Requirements: Operating System: Hardware Required: Software Required: Availability Status: On Request Documentation Available:

This data package includes data files and an R script to reproduce results reported in the paper "Demographic declines and responses of breeding bird populations to human footprint in the Athabasca Oil Sands Region, Alberta, Canada". Analyses include hierarchical multispecies models applied to data from 31 bird species at 38 Monitoring Avian Productivity and Survivorship (MAPS) stations to assess 10-year (2011–2020) demographic trends and responses to energy sector disturbance (human footprint proportion) in the Athabasca oil sands region of Alberta, Canada. Adult captures, productivity, and residency probability all declined over the study period, and adult apparent survival probability also tended to decline. Trends in adult captures, productivity, and survival were all more negative at stations with larger increases in disturbance over the study period. Species associated with early seral stages were more commonly captured at more disturbed stations, while species typical of mature f...

Agricultural socialized service is gradually emerging as a new stimulus for enhancing the agricultural production environment. However, their precise impact on improving the agricultural ecological environment and promoting the green development of agriculture remains incompletely understood. Therefore, leveraging panel data spanning from 2003 to 2020 across 31 provinces in China, this study utilizes the bidirectional fixed effect model, moderating effect model, and spatial Durbin model to systematically assess the influence of agricultural socialized services on agricultural green development and its spatial ramifications. The findings show that (I) agricultural socialized services significantly contribute to promoting agricultural green development, particularly in regions with lower aging demographics. (II) The application of the spatial Durbin model reveals that this promotional effect does not exhibit significant spatial spillover effect. (III) The role of agricultural socialized services in fostering agricultural green development can be significantly enhanced by advancements in land transfer, agricultural technological innovations, and the improvement of rural human capital. In conclusion, the study provides a set of policy recommendations that include government financial support, facilitating land transfer, improving rural education and technical training, and promoting green production technologies to effectively promote agricultural green development.

The Canadian Out-of-Employment Panel Survey was conducted by Statistics Canada for Human Resources Development Canada, Strategic Evaluation and Monitoring. This survey interviewed people who had a job interruption during one of the two reference periods: (1) Jan. 29-Mar. 11, 1995; or (2) Apr. 23-June 3, 1995.The survey gathered information on subsequent employment during a 13-month period, background demographics on the individual and the household, as well as information on job search activities and outcomes, income, assets and debts, expenditures, and training.In 1996, the COEP survey was re-designed as the Changes in Employment Survey, referred to as COEP 1996. The re-designed survey had changes in the sample design and content to allow a more complete picture of the population of individuals experiencing a loss or change of employment. The survey collects information on employment history during an 18-month period, background demographics on the individual and the household, as well as information on job search activities and outcomes, income, assets and debts, expenditures, and training.The main changes to the sample design compared to COEP 1995 are as follows: all individuals who are issued an ROE in the reference period are included in the 1996 design whereas under the 1995 design, only individuals whose ROE was issued for particular reasons were included; and the reference periods for the 1996 design are consecutive quarters, giving complete coverage across time whereas for the 1995 design, two discrete time periods were selected.The main change to the content compared to COEP 1995 is as follows: information is collected about all employers the individual worked for during the reference period whereas under the 1995 design, information was only collected for the ROE employer, the next employer and the current employer.