The General Social Surveys (GSS) have been conducted by the National Opinion Research Center (NORC) annually since 1972, except for the years 1979, 1981, and 1992 (a supplement was added in 1992), and biennially beginning in 1994. The GSS are designed to be part of a program of social indicator research, replicating questionnaire items and wording in order to facilitate time-trend studies. This data file has all cases and variables asked on the 2022 GSS.

The 2022 cross-sectional General Social Survey has been updated to Release Version 3a as of May 2024. This Release includes the addition of an oversample of minorities (based on the AmeriSpeak® Panel), household composition and respondent selection data, and post-stratified weights for all years of the GSS.

To download syntax files for the GSS that reproduce well-known religious group recodes, including RELTRAD, please visit the "/research/syntax-repository-list" Target="_blank">ARDA's Syntax Repository.

The General Social Surveys (GSS) have been conducted by the National Opinion Research Center (NORC) annually since 1972, except for the years 1979, 1981, and 1992 (a supplement was added in 1992), and biennially beginning in 1994. The GSS are designed to be part of a program of social indicator research, replicating questionnaire items and wording in order to facilitate time-trend studies. This data file has all cases and variables asked on the 2014 GSS. There are a total of 3,842 cases in the data set but their initial sampling years vary because the GSS now contains panel cases. Sampling years can be identified with the variable SAMPTYPE.

To download syntax files for the GSS that reproduce well-known religious group recodes, including RELTRAD, please visit the "/research/syntax-repository-list" Target="_blank">ARDA's Syntax Repository.

This file contains all of the cases and variables that are in the original 2014 General Social Survey, but is prepared for easier use in the classroom. Changes have been made in two areas. First, to avoid confusion when constructing tables or interpreting basic analysis, all missing data codes have been set to system missing. Second, many of the continuous variables have been categorized into fewer categories, and added as additional variables to the file.

The General Social Surveys (GSS) have been conducted by the National Opinion Research Center (NORC) annually since 1972, except for the years 1979, 1981, and 1992 (a supplement was added in 1992), and biennially beginning in 1994. The GSS are designed to be part of a program of social indicator research, replicating questionnaire items and wording in order to facilitate time-trend studies. This data file has all cases and variables asked on the 2014 GSS. There are a total of 3,842 cases in the data set but their initial sampling years vary because the GSS now contains panel cases. Sampling years can be identified with the variable SAMPTYPE.

To download syntax files for the GSS that reproduce well-known religious group recodes, including RELTRAD, please visit the "/research/syntax-repository-list" Target="_blank">ARDA's Syntax Repository.

GSS Deer Detection

## Overview

GSS Deer Detection is a dataset for object detection tasks - it contains Deer annotations for 744 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Abstract

The 2022 Ghana Demographic and Health Survey (2022 GDHS) is the seventh in the series of DHS surveys conducted by the Ghana Statistical Service (GSS) in collaboration with the Ministry of Health/Ghana Health Service (MoH/GHS) and other stakeholders, with funding from the United States Agency for International Development (USAID) and other partners.

The primary objective of the 2022 GDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the GDHS collected information on: - Fertility levels and preferences, contraceptive use, antenatal and delivery care, maternal and child health, childhood mortality, childhood immunisation, breastfeeding and young child feeding practices, women’s dietary diversity, violence against women, gender, nutritional status of adults and children, awareness regarding HIV/AIDS and other sexually transmitted infections, tobacco use, and other indicators relevant for the Sustainable Development Goals - Haemoglobin levels of women and children - Prevalence of malaria parasitaemia (rapid diagnostic testing and thick slides for malaria parasitaemia in the field and microscopy in the lab) among children age 6–59 months - Use of treated mosquito nets - Use of antimalarial drugs for treatment of fever among children under age 5

The information collected through the 2022 GDHS is intended to assist policymakers and programme managers in designing and evaluating programmes and strategies for improving the health of the country’s population.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Man age 15-59

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49, men aged 15-59, and all children aged 0-4 resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

To achieve the objectives of the 2022 GDHS, a stratified representative sample of 18,450 households was selected in 618 clusters, which resulted in 15,014 interviewed women age 15–49 and 7,044 interviewed men age 15–59 (in one of every two households selected).

The sampling frame used for the 2022 GDHS is the updated frame prepared by the GSS based on the 2021 Population and Housing Census.1 The sampling procedure used in the 2022 GDHS was stratified two-stage cluster sampling, designed to yield representative results at the national level, for urban and rural areas, and for each of the country’s 16 regions for most DHS indicators. In the first stage, 618 target clusters were selected from the sampling frame using a probability proportional to size strategy for urban and rural areas in each region. Then the number of targeted clusters were selected with equal probability systematic random sampling of the clusters selected in the first phase for urban and rural areas. In the second stage, after selection of the clusters, a household listing and map updating operation was carried out in all of the selected clusters to develop a list of households for each cluster. This list served as a sampling frame for selection of the household sample. The GSS organized a 5-day training course on listing procedures for listers and mappers with support from ICF. The listers and mappers were organized into 25 teams consisting of one lister and one mapper per team. The teams spent 2 months completing the listing operation. In addition to listing the households, the listers collected the geographical coordinates of each household using GPS dongles provided by ICF and in accordance with the instructions in the DHS listing manual. The household listing was carried out using tablet computers, with software provided by The DHS Program. A fixed number of 30 households in each cluster were randomly selected from the list for interviews.

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

Mode of data collection

Face-to-face computer-assisted interviews [capi]

Research instrument

Four questionnaires were used in the 2022 GDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Biomarker Questionnaire. The questionnaires, based on The DHS Program’s model questionnaires, were adapted to reflect the population and health issues relevant to Ghana. In addition, a self-administered Fieldworker Questionnaire collected information about the survey’s fieldworkers.

The GSS organized a questionnaire design workshop with support from ICF and obtained input from government and development partners expected to use the resulting data. The DHS Program optional modules on domestic violence, malaria, and social and behavior change communication were incorporated into the Woman’s Questionnaire. ICF provided technical assistance in adapting the modules to the questionnaires.

Cleaning operations

DHS staff installed all central office programmes, data structure checks, secondary editing, and field check tables from 17–20 October 2022. Central office training was implemented using the practice data to test the central office system and field check tables. Seven GSS staff members (four male and three female) were trained on the functionality of the central office menu, including accepting clusters from the field, data editing procedures, and producing reports to monitor fieldwork.

From 27 February to 17 March, DHS staff visited the Ghana Statistical Service office in Accra to work with the GSS central office staff on finishing the secondary editing and to clean and finalize all data received from the 618 clusters.

Response rate

A total of 18,540 households were selected for the GDHS sample, of which 18,065 were found to be occupied. Of the occupied households, 17,933 were successfully interviewed, yielding a response rate of 99%. In the interviewed households, 15,317 women age 15–49 were identified as eligible for individual interviews. Interviews were completed with 15,014 women, yielding a response rate of 98%. In the subsample of households selected for the male survey, 7,263 men age 15–59 were identified as eligible for individual interviews and 7,044 were successfully interviewed.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors and (2) sampling errors. Nonsampling 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 2022 Ghana Demographic and Health Survey (2022 GDHS) to minimize this type of error, nonsampling 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 2022 GDHS is only one of many samples that could have been selected from the same population, using the same design and identical 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. A 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 2022 GDHS sample was the result of a multistage stratified design, and, consequently, it was necessary to use more complex formulas. The computer software used to calculate sampling errors for the GDHS 2022 is an SAS program. This program used the Taylor linearization method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

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

Data appraisal

Data Quality Tables

• Age distribution of eligible and interviewed women
• Age distribution of eligible and interviewed men
• Age displacement at age 14/15
• Age displacement at age 49/50
• Pregnancy outcomes by years preceding the survey
• Completeness of reporting
• Standardisation exercise results from anthropometry training
• Height and weight data completeness and quality for children
• Height measurements from random subsample of measured children
• Interference in height and weight measurements of children
• Interference in height and weight measurements of women and men
• Heaping in anthropometric measurements for children (digit preference)
• Observation of mosquito nets
• Observation of handwashing facility
• School attendance by single year of age
• Vaccination cards photographed
• Number of

Coriell (Small Models)

## Overview

Coriell (Small Models) is a dataset for object detection tasks - it contains Animals annotations for 1,396 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Ism

## Overview

Ism is a dataset for object detection tasks - it contains Object annotations for 1,986 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

This zip file contains the Code History Database for the United Kingdom as at September 2017. To download the zip file click the Download button. 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 Parishes (E04) and Communities (W04), Wards (W05). Updates to LEPS (37), LEPOPs (E52), LEPNOPs (E53), LRFs (E48) and Development Corporations (E51).· Changes to the Information table.Database Changes· Updates to form design to account for September 2017 version have been made.

🇬🇧 영국 English This zip file contains the Code History Database for the United Kingdom as at September 2017. To download the zip file click the Download button. 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 Parishes (E04) and Communities (W04), Wards (W05). Updates to LEPS (37), LEPOPs (E52), LEPNOPs (E53), LRFs (E48) and Development Corporations (E51).· Changes to the Information table.

Deer Detection Model

## Overview

Deer Detection Model is a dataset for object detection tasks - it contains Objects annotations for 3,463 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

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.

The General Social Surveys (GSS) have been conducted by the National Opinion Research Center annually since 1972, except for the years 1979, 1981, and 1992 (a supplement was added in 1992), and biennially beginning in 1994. The GSS are designed as part of a program of social indicator research, replicating questionnaire items and wording in order to facilitate time-trend studies. Items on religion include religious preference, church attendance, beliefs about the Bible, attitudes toward organized religion and its opponents, and more. The survey also contains a topical module on culture.

To download syntax files for the GSS that reproduce well-known religious group recodes, including RELTRAD, please visit the "/research/syntax-repository-list" Target="_blank">ARDA's Syntax Repository.

Abstract

Following the pattern set in the first two rounds of the Ghana Living Standards Survey (GLSS), the questionnaire used for the third round again covered a wide spectrum of topics such as education, health, housing, employment, income and expenditure, which affect the living standards of households. GLSS III thus provides data on various aspects of Ghanaian household economic and social activities, which are of help for monitoring the impact of the Government's Economic Recovery Programme.

GLSS III differed from the two previous rounds, however, in concentrating particularly on the income, consumption and expenditure of households at a much more disaggregated level than previously. As a result, GLSS III provides more accurate estimates of income and expenditure, including the imputed value of home produced food which is consumed by households. The data on household expenditure are also being used to derive the weights needed for rebasing the Consumer Price Index. The GLSS data on income, consumption and expenditure, together with other individual, household and community level data collected in GLSS III, will also provide a valuable database for national and regional planning purposes. Detailed anthropometric data had been collected in GLSS I and GLSS II, involving the need to include an anthropometrist in each survey team. This topic had to be dropped from GLSS III, so that the expanded income, consumption and expenditure data could be collected.

Geographic coverage

National

Analysis unit

• Household
• Individual
• Community
• Commodity

Kind of data

Sample survey data [ssd]

Sampling procedure

A multi-stage sampling technique was used in selecting the GLSS sample. Initially, 4565 households were selected for GLSS III, spread around the country in 407 small clusters. in general, 15 households were taken in an urban cluster and 10 households in a rural cluster. The actual achieved sample was 4552 households. Because of the sample design used, and the very high response rate, the sample can be considered as being self-weighting, though in the case of expenditure data, weighting of the expenditure values is required.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three types of questionnaires were used for GLSS III: a household questionnaire, a community questionnaire and a price questionnaire.

• The household questionnaire consists of two parts. Part A collected information on household composition, education, health and fertility, employment and time use, migration, and housing characteristics, and it was also used to identify the respondents for Part B. Part B covered agricultural activities, including the consumption of home produce, household expenditure, non-farm enterprises, other income and expenditure, and credit, assets, and savings.

• All urban households were given a special diary, and requested to record on a separate page each day all the expenses they incurred. This had to be done by a literate member of the household who had already been identified during the listing exercise. In the case of illiterate households the supervisor or the supplementary interviewer visited them and did the recording. Although to a large extent the use of diaries seems to have served its intended purpose of facilitating the recording of expenditures for many urban households, some caution has to be taken in interpreting the results and estimates derived from the diaries. In particular, while most of the expenses incurred by the household as a unit are likely to have been recorded fairly accurately, it is possible that some of the expenses made by individual members of the household outside the home may have been missed.

• Details of infrastructure and other facilities available to rural communities were recorded in the community questionnaire. This questionnaire was usually administered at a meeting with the community chief, along with his elders and other knowledgeable people in the community.

• The price questionnaire was used to collect information on prices in the local market. This information is needed for comparing prices in different parts of the country, which would allow the construction of regional price indexes and the adjustment of household expenditures to a common base so as to take account of regional variations in purchasing power.

Cleaning operations

The data collected in this survey were entered directly onto microcomputers which had been installed in the eight regional capitals. Kumasi and Accra had two PCs each, while Tamale, Sunyani, Koforidua, Ho, Cape Coast and Sekondi/Takoradi had one each. Special interactive software programs had been prepared for data entry and checking, using the software package Rode-PC. Data entry was done in two rounds. In both urban and rural clusters interviewers completed Part A of the questionnaire by the end of the fifth visit to each household; and after checking them, the supervisor took these questionnaires straight away to the regional capital, where the data entry operator began keying in. Once Part B had been completed, the supervisor took these questionnaires to the regional capital, and returned with the Part A questionnaires, plus detailed printouts showing what errors had been discovered by the editing program during the keying in operation. These errors were then corrected in the field. By the time the data entry operator had finished keying in the second batch of questionnaires (Part B), the team would have moved from those clusters to the next set of clusters. However, the next set of clusters were very close to the previous ones, so going back to correct errors detected in the second round involved travelling only a short distance. This arrangement made field reconciliation fairly easy. In addition, each set of clusters had been chosen close together so as to make supervision relatively easy. Finally, clusters in areas that were hardly accessible during the rainy season were scheduled to be covered during the dry season. At regular intervals during the fieldwork the diskettes containing the GLSS III data for each completed cycle were returned to the headquarters in Accra. Final tabulations were produced using the SAS software package.

This file differs from the General Social Survey 2014 in that all inapplicable values are set to system missing. The General Social Surveys (GSS) have been conducted by the National Opinion Research Center (NORC) annually since 1972, except for the years 1979, 1981, and 1992 (a supplement was added in 1992), and biennially beginning in 1994. The GSS are designed to be part of a program of social indicator research, replicating questionnaire items and wording in order to facilitate time-trend studies. This data file has all cases and variables asked on the 2014 GSS. There are a total of 3,842 cases in the data set but their initial sampling years vary because the GSS now contains panel cases. Sampling years can be identified with the variable SAMPTYPE.

To download syntax files for the GSS that reproduce well-known religious group recodes, including RELTRAD, please visit the "/research/syntax-repository-list" Target="_blank">ARDA's Syntax Repository.

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.