The public use microdata file (PUMF) from the General Social Survey – Canadians' Safety is to better understand how Canadians perceive crime and the justice system and to capture information on their experiences of victimization. This survey is the only national survey of self-reported victimization and is collected in all provinces and territories. The survey allows for estimates of the numbers and characteristics of victims and criminal incidents. Topics covered are: neighbourhood safety, crime prevention, risks and perceptions, abuse by current spouse/partner, crime incidents, criminal harassment, confidence in police, hate crimes, cyber bullying, experiences of discrimination, health and well-being and also a variety of socio-demographic measures. Cycle 34 is the seventh cycle of the GSS to collect data on victimization. Previous cycles were conducted in 1988, 1993, 1999, 2004, and 2009, 2014.

In 2023, Europe accounted for *********** of the total value of green, social, sustainability, and sustainability-linked (GSSS) bonds issued worldwide. Europe has been the leading issuer of GSSS bonds since their inception. Asia-Pacific was the second-largest contributor to GSSS issuance, accounting for ** percent of the total in 2023.

The Graduate Students and Postdoctorates in Science and Engineering survey is an annual census of all U.S. academic institutions granting research-based master's degrees or doctorates in science, engineering, and selected health fields as of fall of the survey year. The survey, sponsored by the National Center for Science and Engineering Statistics within the National Science Foundation and by the National Institutes of Health, collects the total number of master's and doctoral students, postdoctoral appointees, and doctorate-level nonfaculty researchers by demographic and other characteristics such as source of financial support. Results are used to assess shifts in graduate enrollment and postdoc appointments and trends in financial support. This dataset includes GSS assets for 2019.

The main objective of the GSS on Canadians' Safety is to better understand how Canadians perceive crime and the justice system and to capture information on their experiences of victimization. This survey is the only national survey of self-reported victimization and is collected in all provinces and territories. The survey allows for estimates of the numbers and characteristics of victims and criminal incidents. As not all crimes are reported to the police, the survey provides an important complement to officially recorded crime rates. It measures both crime incidents that come to the attention of the police and those that are unreported. It also helps to understand the reasons behind whether or not people report a crime to the police. Survey results will be used by police departments, all levels of government, victim and social service agencies, community groups and researchers not only to better understand the nature and extent of victimization in Canada, but also to study Canadians' perceptions of their safety, the levels of crime in their neighbourhoods, and their attitudes toward the criminal justice system.

The Korean General Social Survey (KGSS) is the Korean version of the General Social Survey (GSS) , closely replicating the original GSS of the National Opinion Research Center at the University of Chicago. The KGSS comprises four parts: The first part includes replicating core questions that cover the core content of Korean society. The second part is the International Social Survey Program (ISSP) module, which is a cross-national survey of 43 countries from all over the world. The third part is the East Asian Social Survey (EASS) module. The EASS is a joint survey of four East Asian countries (Korea, Japan, China and Taiwan) conducting a GSS-type social survey. The last part contains modules proposed by researchers. This data collection is the cumulative version of the previous 18 years of survey data from 2003 to 2021 (not including 2015, 2017, 2019 and 2020). This dataset contains a total of 20,841 cases across 3,215 variables. Respondents were asked for their opinions about Korean society, economic conditions, government performance, politics and political conditions. Additional questions were asked regarding the health care system, respondents' health behaviors, human rights, attitudes toward aging and the elderly, household composition, household income, education, occupation, environmental issues, international migration and so on. Demographic information collected includes age, sex, education level, household income, employment status, religious preference, political party affiliation, and political philosophy.

Ghana GSS Projection: Population data was reported at 30,955.202 Person th in 2020. This records an increase from the previous number of 30,280.811 Person th for 2019. Ghana GSS Projection: Population data is updated yearly, averaging 27,989.237 Person th from Dec 2011 (Median) to 2020, with 10 observations. The data reached an all-time high of 30,955.202 Person th in 2020 and a record low of 25,263.597 Person th in 2011. Ghana GSS Projection: Population data remains active status in CEIC and is reported by Ghana Statistical Service. The data is categorized under Global Database’s Ghana – Table GH.G002: Population Projection: by Sex: Ghana Statistical Service.

The National Congregations Study (NCS) dataset fills a void in the sociological study of congregations by providing data that can be used to draw a nationally aggregate picture of congregations. Thanks to innovations in sampling techniques, the 1998 NCS data was the first nationally representative sample of American congregations. Subsequent NCS waves were conducted in 2006-07, 2012, and 2018-19.

Like Wave II, Wave IV again included a panel component. In addition to the new cross-section of congregations generated in conjunction with the 2018 GSS, the NCS-IV included all Wave III congregations that were nominated by GSS respondents who participated in the GSS for the first time in 2012. That is, the panel did not include Wave III congregations that had been nominated by GSS respondents who were in the 2012 GSS because they were part of the GSS's own panel of re-interviewees. The 2018-19 NCS, then, includes a subset of congregations that also were interviewed in 2012. A full codebook, prepared by the primary investigator and containing a section with details about the panel datasets, is available for download "https://sites.duke.edu/ncsweb/files/2020/09/NCS-I-IV-Cumulative-Codebook_FINAL_8Sept2020.pdf" Target="_blank">here. The codebook contains the original questionnaire, as well as detailed information on survey methodology, weights, coding, and more.

The "/data-archive?fid=NCSIV" Target="_blank">NCS Cumulative Dataset is also available from the ARDA.

Abstract

The primary objective of the survey is to provide current estimates of key malaria indicators. Specific objectives were: ▪ To measure the extent of ownership and use of mosquito bed nets ▪ To assess coverage of intermittent preventive treatment to protect pregnant women ▪ To identify practices and specific medications used for treating malaria among children under age 5 ▪ To measure indicators of behaviour change communication messages, knowledge, and practices regarding malaria ▪ To measure the prevalence of malaria and severe anaemia among children age 6-59 months

The findings from the 2019 GMIS will assist policymakers and programme managers in evaluating and designing programmes and strategies for improving malaria control interventions in Ghana.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49

Universe

The survey covered all de jure household members (usual residents), women age 15-49 years and children age 6-59 months resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for the 2019 GMIS was designed to provide estimates of key malaria indicators for the country as a whole, for urban and rural areas separately, and for each of the 10 administrative regions (Western, Central, Greater Accra, Volta, Eastern, Ashanti, Brong Ahafo, Northern, Upper East, and Upper West) as defined in the Ghana 2010 Population and Housing Census (PHC).

The sampling frame used for the 2019 GMIS is the frame of the 2010 PHC, conducted in Ghana by GSS. In 2019, Ghana created six new regions, resulting in a total of 16 regions and 260 administrative districts; however, during survey design, the new administrative boundaries were not available. The 2019 GMIS sampling frame is therefore based on the 10 regional boundaries defined according to the 2010 PHC. The frame is a complete list of all census enumeration areas (EAs) created for the PHC. An EA is the smallest geographic area that can be easily canvassed by an enumerator during an enumeration exercise. The sampling frame contains information about EA location, type of residence (urban or rural), the estimated number of residential households, and the estimated population.

The 2019 GMIS sample was stratified and selected from the sampling frame in two stages. In the first stage, 200 EAs (97 in urban areas and 103 in rural areas) were selected with probability proportional to EA size and with independent selection in each sampling stratum. In the second stage of selection, a fixed number of 30 households was selected from each cluster to make up a total sample size of 6,000 households.

For further details on sample design, see Appendix A of the final report.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Four types of questionnaires were used for the 2019 GMIS: the Household Questionnaire, the Woman’s Questionnaire, the Biomarker Questionnaire, and the Fieldworker Questionnaire. The questionnaires were adapted to reflect issues relevant to Ghana. Modifications were determined after a series of meetings with various stakeholders from the NMCP and other government ministries and agencies, nongovernmental organisations, and international partners. The Household and Woman’s Questionnaires in English and four local Ghanaian languages (Akan, Dagbani, Ewe, and Ga) were programmed into tablet computers, which enabled the use of computer-assisted personal interviewing for the survey. The Biomarker Questionnaire, also translated into four local languages, was filled out on hard copy and entered into the CAPI system when complete.

Cleaning operations

Data for the 2019 GMIS were collected through questionnaires programmed into the CAPI application. The CAPI application was programmed by The DHS Program and loaded into the computers along with the Household, Biomarker, and Woman’s Questionnaires. Using the Internet File Streaming System (IFSS) developed by The DHS Program, the field supervisors transferred data on a daily basis to a central location for data processing in the GSS office located in Accra. To facilitate communication and monitoring, each fieldworker was assigned a unique identification number.

The Census and Survey Processing (CSPro) program was used for data editing, cleaning, weighting, and tabulation. Data received from the field teams’ CAPI applications were registered and checked for any inconsistencies and outliers at the GSS Head Office. Data editing and cleaning included an extensive range of structural and internal consistency checks. All anomalies were communicated to field teams, which resolved data discrepancies. The corrected results were maintained in master CSPro data files and then used in producing tables for the final report.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: non-sampling errors and sampling errors. Non-sampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2019 Ghana Malaria Indicator Survey (GMIS) to minimize this type of error, non-sampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2019 GMIS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

Sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2019 GMIS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS, using programs developed by ICF. These programs use the Taylor linearization method of variance estimation for survey estimates that are means, proportions, or ratios.

A more detailed description of estimates of sampling errors are presented in Appendix B of the survey report.

Data appraisal

Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Completeness of reporting - Births by calendar years - Number of enumeration areas completed by month, according to region, Ghana MIS 2019 - Percentage of children age 6-59 months classified as having malaria according to rapid diagnostic test (RDT), by month and region, Ghana MIS 2019 - Number of children age 6-59 months measured for malaria via rapid diagnostic test (RDT), by month and region (unweighted), Ghana MIS 2019

See details of the data quality tables in Appendix C of the final report.

Indigenous people are overrepresented in Canada's criminal justice system as both victims and as people accused or convicted of crime. There are only a few national data sources that provide criminal justice statistics disaggregated by Indigenous identity. National data that does exist to identify Indigenous people in the criminal justice system include the General Social Survey (GSS) on self-reported victimization, police-reported homicide statistics, and data on provincial/territorial and federal custody. This fact sheet uses data from the 2014 General Social Survey (GSS) on Victimization. Every five years, the GSS on Criminal Victimization presents data on Canadians aged 15 years and older who report having been victimized in the previous twelve months. For comparison’s sake, the survey focuses on eight specific categories of crime: sexual assault, robbery, physical assault, theft of personal property, break and enter, theft of motor vehicle or parts, theft of household property, and vandalism. This fact sheet also uses data from special studies conducted by the Canadian Centre for Justice Statistics at Statistics Canada, Statistics Canada’s Homicide Survey, and the correctional surveys from Statistics Canada: Adult Correctional Services Survey (ACS); Integrated Correctional Services Survey (ICSS); and Canadian Correctional Services Survey (CCSS).

Indigenous people are overrepresented in Canada's criminal justice system as both victims and as people accused or convicted of crime. There are only a few national data sources that provide criminal justice statistics disaggregated by Indigenous identity. National data that does exist to identify Indigenous people in the criminal justice system include the General Social Survey (GSS) on self-reported victimization, police-reported homicide statistics, and data on provincial/territorial and federal custody. This fact sheet uses data from the 2014 General Social Survey (GSS) on Victimization. Every five years, the GSS on Criminal Victimization presents data on Canadians aged 15 years and older who report having been victimized in the previous twelve months. For comparison’s sake, the survey focuses on eight specific categories of crime: sexual assault, robbery, physical assault, theft of personal property, break and enter, theft of motor vehicle or parts, theft of household property, and vandalism. This fact sheet also uses data from special studies conducted by the Canadian Centre for Justice Statistics at Statistics Canada, Statistics Canada’s Homicide Survey, and the correctional surveys from Statistics Canada: Adult Correctional Services Survey (ACS); Integrated Correctional Services Survey (ICSS); and Canadian Correctional Services Survey (CCSS).

Ghana GSS Projection: Population: Female data was reported at 15,231.056 Person th in 2020. This records a decrease from the previous number of 15,392.003 Person th for 2019. Ghana GSS Projection: Population: Female data is updated yearly, averaging 14,264.824 Person th from Dec 2011 (Median) to 2020, with 10 observations. The data reached an all-time high of 15,392.003 Person th in 2019 and a record low of 12,929.830 Person th in 2011. Ghana GSS Projection: Population: Female data remains active status in CEIC and is reported by Ghana Statistical Service. The data is categorized under Global Database’s Ghana – Table GH.G002: Population Projection: by Sex: Ghana Statistical Service.

The National Congregations Study (NCS) is a national survey effort to gather information about America's congregations. The first wave of the NCS took place in 1998, and the study was repeated in 2006-07, 2012, and 2018-19. The NCS tracks continuity and change among American congregations, and each NCS wave also explores new subjects. With information from 5,333 congregations collected over a span of more than 20 years, the NCS helps us better understand many aspects of congregational life in the United States, and how congregations are changing in the 21st century. The NCS contributes to knowledge about American religion by collecting information about a wide range of congregations' characteristics and activities at different points in time. In all four waves, the NCS was conducted in conjunction with the General Social Survey (GSS). The 1998, 2006, 2012, and 2018 waves of the GSS asked respondents who attend religious services to name their congregation, thus generating a nationally representative sample of religious congregations. Researchers then located these congregations. In 2006, the sample included re-interviews of a subset of congregations that participated in 1998, and in 2018-19, the sample included re-interviews of a subset of congregations that participated in 2012. A key informant at each congregation - a minister, priest, rabbi, or other staff person or leader - provided each congregation's information via a one-hour interview conducted either over the phone or in-person. The survey gathered information on many topics, including the congregation's leadership, social composition, structure, activities, and programming. The NCS gathers information about worship, programs, staffing, community activities, demographics, funding, and many other characteristics of American congregations. Respondents of the NCS survey were asked to describe the worship service and programs sponsored by the congregation other than the main worship services, including religious education classes, musical groups, and recreational programs. Informants described the type of building in which the congregation met, whether it belonged to the congregation, and whether visitors came just to view the building's architecture or artwork. Congregations were geocoded, and selected census variables are included in this study.

Ghana GSS Projection: Population: Male data was reported at 15,724.146 Person th in 2020. This records an increase from the previous number of 14,888.808 Person th for 2019. Ghana GSS Projection: Population: Male data is updated yearly, averaging 13,724.414 Person th from Dec 2011 (Median) to 2020, with 10 observations. The data reached an all-time high of 15,724.146 Person th in 2020 and a record low of 12,333.767 Person th in 2011. Ghana GSS Projection: Population: Male data remains active status in CEIC and is reported by Ghana Statistical Service. The data is categorized under Global Database’s Ghana – Table GH.G002: Population Projection: by Sex: Ghana Statistical Service.

Abstract

the 2019 Ghana Malaria Indicator Survey (GMIS) was the second in the series; the first was conducted in 2016. The 2019 GMIS was a national survey designed to obtain population-based estimates of malaria indicators to complement routine administrative data that are used to inform strategic planning and evaluation of the Ghana Malaria Control Programme.

The survey provides information on malaria prevention, treatment, and prevalence in Ghana. More specifically, the survey collected data on ownership and use of mosquito bed nets, assessed coverage of intermittent preventive treatment to protect pregnant women against malaria, identified practices and specific medications used to treat malaria, measured indicators of malaria knowledge and communication messages, and estimated the prevalence of malaria and anaemia among children age 6-59 months.

Geographic coverage

National Coverage

Universe

All women age 15-49 who were either permanent residents of the selected households or visitors who stayed in the household the night before the survey were eligible to be interviewed. With the parent’s or guardian’s consent, children age 6-59 months were tested for anaemia and malaria infection.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for the 2019 GMIS was designed to provide estimates of key malaria indicators for the country as a whole, for urban and rural areas separately, and for each of the 10 administrative regions (Western, Central, Greater Accra, Volta, Eastern, Ashanti, Brong Ahafo, Northern, Upper East, and Upper West) as defined in the Ghana 2010 Population and Housing Census (PHC).

The sampling frame used for the 2019 GMIS is the frame of the 2010 PHC, conducted in Ghana by GSS. In 2019, Ghana created six new regions, resulting in a total of 16 regions and 260 administrative districts; however, during survey design, the new administrative boundaries were not available. The 2019 GMIS sampling frame is therefore based on the 10 regional boundaries defined according to the 2010 PHC. The frame is a complete list of all census enumeration areas (EAs) created for the PHC. An EA is the smallest geographic area that can be easily canvassed by an enumerator during an enumeration exercise. The sampling frame contains information about EA location, type of residence (urban or rural), the estimated number of residential households, and the estimated population.

The 2019 GMIS sample was stratified and selected from the sampling frame in two stages. Each region was divided into urban and rural areas; this yielded 20 sampling strata. Samples of EAs were selected independently in each stratum in two stages. Implicit stratification with proportional allocation was achieved at each of the lower administrative levels by sorting the sampling frame within each sampling stratum before sample selection, according to administrative units at different levels, and by using a probability proportional to size selection in the first stage of sampling.

In the first stage, 200 EAs (97 in urban areas and 103 in rural areas) were selected with probability proportional to EA size and with independent selection in each sampling stratum. A household listingoperation was conducted from 24 June to 10 August 2019 in all of the selected EAs. The list of households was directly recorded on tablet PCs, using the computer-assisted personal interviewing (CAPI) system, and this list served as a sampling frame for the selection of households in the second stage. Some of the selected EAs were very large. To minimise the task of household listing, each large EA selected for the 2019 GMIS was segmented. Only one segment was selected for the survey with probability proportional to segment size. Household listing was conducted only in the selected segment. Thus, in the 2019 GMIS, a cluster is either an EA or a segment of an EA. As part of the listing, the field teams updated the necessary maps and recorded the geographic coordinates of each cluster. The listing was conducted by 10 teams that included one lister/team leader, one mapper, and a driver.

In the second stage of selection, a fixed number of 30 households was selected from each cluster to make up a total sample size of 6,000 households. Replacement of non-responding households was not allowed. Due to the non-proportional allocation of the sample to the different regions and the possible differences in response rates, sampling weights are required for any analysis that uses the 2019 GMIS data. This ensures the actual representation of the survey results at the national and regional levels. Results shown in this report have been weighted to account for the complex sample design. More information on weight calculation is presented in Appendix A in the final report.

All women age 15-49 who were either permanent residents of the selected households or visitors who stayed in the household the night before the survey were eligible to be interviewed. With the parent’s or guardian’s consent, children age 6-59 months were tested for anaemia and malaria infection.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Four types of questionnaires were used for the 2019 GMIS: the Household Questionnaire, the Woman’s Questionnaire, the Biomarker Questionnaire, and the Fieldworker Questionnaire. The questionnaires were adapted to reflect issues relevant to Ghana. Modifications were determined after a series of meetings with various stakeholders from the NMCP and other government ministries and agencies, nongovernmental organisations, and international partners. The Household and Woman’s Questionnaires in English and four local Ghanaian languages (Akan, Dagbani, Ewe, and Ga) were programmed into tablet computers, which enabled the use of computer-assisted personal interviewing for the survey. The Biomarker Questionnaire, also translated into four local languages, was filled out on hard copy and entered into the CAPI system when complete.

The Household Questionnaire was used to list all of the usual members of and visitors to the selected households. Basic information was collected on the characteristics of each person listed in the household, including age, sex, and relationship to the head of the household. The data on age and sex of household members obtained from the questionnaire were used to identify women eligible for individual interviews and children age 6-59 months eligible for anaemia and malaria testing. Additionally, the Household Questionnaire captured information on characteristics of the household’s dwelling unit, such as source of water, type of toilet facilities, materials used for the floor, ownership of various durable goods, and ownership and use of mosquito nets.

The Woman’s Questionnaire was used to collect information from women age 15-49. These women were asked questions on the following topics: - Background characteristics (age, education, literacy, religion, and ethnicity) - Reproductive history for the last 5 years - Preventive malaria treatment during the pregnancy of the most recent live birth - Prevalence and treatment of fever among children under age 5 - Knowledge about malaria (symptoms, causes, prevention, and types of antimalarial medications) - Exposure to and source of media messages about malaria in the last 6 months

The Biomarker Questionnaire was used to record the results of the anaemia and malaria testing of children age 6-59 months.

The purpose of the Fieldworker Questionnaire was to collect basic background information on the people who collected data in the field, including the team supervisors, interviewers, and health technicians. This self-administered questionnaire was created to serve as a tool in conducting analyses of data quality. The questionnaire was distributed and collected by the GSS after final selection of fieldworkers and before the fieldworkers entered the field. No personal identifiers were attached to the GMIS fieldworkers’ data file.

Cleaning operations

Data for the 2019 GMIS were collected through questionnaires programmed into the CAPI application. The CAPI application was programmed by The DHS Program and loaded into the computers along with the Household, Biomarker, and Woman’s Questionnaires. Using the Internet File Streaming System (IFSS) developed by The DHS Program, the field supervisors transferred data on a daily basis to a central location for data processing in the GSS office located in Accra. To facilitate communication and monitoring, each fieldworker was assigned a unique identification number.

The Census and Survey Processing (CSPro) program was used for data editing, cleaning, weighting, and tabulation. Data received from the field teams’ CAPI applications were registered and checked for any inconsistencies and outliers at the GSS Head Office. Data editing and cleaning included an extensive range of structural and internal consistency checks. All anomalies were communicated to field teams, which resolved data discrepancies. The corrected results were maintained in master CSPro data files and then used in producing tables for the final report.

Response rate

A total of 6,002 households were selected for the survey, of which 5,833 were occupied at the time of fieldwork. Among the occupied households, 5,799 were successfully interviewed, yielding a response rate of 99%. In the interviewed households, 5,246 eligible women were identified for individual interviews and 5,181 were successfully interviewed, yielding a response rate of 99%.

Data in this fact sheet are from the Uniform Crime Reporting Survey (UCR) and the 2019 General Social Survey on Canadians’ Safety (also known as the GSS on Victimization). The UCR Survey collects data on police-reported crime and the GSS on Victimization collects self-reported data on victimization from those aged 15 years and older living in the provinces and territories. This fact sheet focuses on police-reported hate crime and, primarily, violent hate crime.2 A hate crime is defined in the UCR as a criminal violation motivated by hate, based on race, national or ethnic origin, language, colour, religion, sex, age, mental or physical disability, sexual orientation or gender identity or expression, or any other similar factor. Victims are only identified in the UCR where there is a violent offence.

Cette statistique indique quels organismes récupéraient les produits invendus auprès des grandes surfaces spécialisées en 2018 et 2019. Dans près de ** % des GSS prises en compte lors du sondage, des associations s'occupaient de la collecte de dons.

This zip file contains the Code History Database for the United Kingdom as at June 2019. To download the zip file click the Download button. BUG FIX (29th July 2019)A bug was identified in one of the queries that was used to create the equivalents listings within the database. This has now been fixed and the Code History Database is running correctly as of 29th July 2019.Updates to Changes.csv and Equivalents.csv have been made and re-issued within the downloadable ZIP file as a result of this bug fix.The Code History Database (CHD) contains the GSS nine-character codes, where allocated, for current and new statistical geographies from 1 January 2009. The codes consist of a simple alphanumeric structure; the first three characters (ANN) represent the area entity (i.e. type; or category of geography) and the following six characters (NNNNNN) represent the specific area instance. The CHD provides multiple functionality including details of codes, relationships, hierarchies and archived data. The CHD can be used in conjunction with the Register of Geographic Codes (RGC) that summarises the range of area instances within each geographic entity. The GSS Coding and Naming policy for some statistical geographies was implemented on 1 January 2011. From this date, where new codes have been allocated they should be used in all exchanges of statistics and published outputs that normally include codes. For further information on this product, please read the user guide and version notes contained within the product zip file.Updated Geographies• Updates to Civil Parishes (E04), Electoral Wards/Division (E05), Unitary Authorities (E06), Non-metropolitan districts (E07), Counties (E10), Registration Districts (E28), Registration Sub-district (E29), Clinical Commissioning Groups (E38), NHS England (Region, Local Office) (E39), NHS England Regions (E40), Non-Civil Parishes Areas (E43), Combined Authorities (E47) and Cancer Alliances (E56) in England• Updates to Health Board areas (S08), Council Areas (S12), Local Administrative Units 1 (S30), Scottish Police Divisions (S32), Integration Authorities (S37), Scottish Fire and Rescue Local Senior Officer Areas (S39) in Scotland.• Updates to Local Health Boards (W11) in Wales. • New Geography Entities - Local Planning Authorities (E60) and Greater London Authority (E61). • New Geography Entity – Local Planning Authorities (N13)• New Geography Entities - Scottish Local Resilience Partnerships (S42), Scottish Regional Resilience Partnerships (S43) and Local Planning Authorities (S44).• New Geography Entity - Local Planning Authorities (W44)• National Cancer Vanguards (E57) abolished

Cette statistique indique le niveau de connaissance de la RSE par les grandes et moyennes surfaces spécialisées en France entre 2018 et 2019. Il en ressort que la quasi-majorité des responsables de GSS n'avaient aucune idée de ce qu'était la responsabilité sociétale des entreprises. Seulement * % des personnes interrogées avaient une idée claire et précise de la RSE.

This dataset contains U-Pb isotopic data and associated ages of zircons from selected igneous rocks collected from the region surrounding and including the uplands of the United States Territory of Puerto Rico. The samples were collected as part of geological mapping and research conducted during 2018 and funded by the Mineral Resources Program of the U.S. Geological Survey. Zircon grains were separated and analyzed by GeoSep Services (GSS) in 2019 using laser-ablation-inductively-coupled-plasma-mass spectrometry (LA-ICP-MS) techniques.