A. SUMMARY This dataset contains San Francisco Board of Supervisor district boundaries approved by the San Francisco Redistricting Task Force in April 2022 following redistricting based on the 2020 Decennial Census. B. HOW THE DATASET IS CREATED The dataset was created from the final map submitted by the San Francisco Redistricting Task Force. Boundaries in this map were decided using data from the 2020 Census on the number of people living in each census block in the City and County. This data includes the number of individuals incarcerated in facilities under the control of the Department of Corrections and Rehabilitation based on their last known residential address. This information is made available by the Statewide Database based on U.S. Census Bureau Census Redistricting Data (P.L. 94-171). These map boundaries were trimmed to align with the city and county's physical boundaries for greater usability. This trimming mainly consisted of excluding the water around the City and County from the boundaries. C. UPDATE PROCESS Supervisor District boundaries are updated every 10 years following the federal decennial census. The Supervisor District boundaries reflected in this dataset will remain unchanged. A new dataset will be created after the next decennial census and redistricting process are completed. The dataset is manually updated as new members of the Board of Supervisors take office. The most recent manual update date is reflected in the 'data_as_of' field. Once the redistricting process is completed after the next decennial census and a new dataset is published, this dataset will become static and will no longer be updated. D. HOW TO USE THIS DATASET This dataset can be joined to other datasets for analysis and reporting at the Supervisor District level. If you are building an automated reporting pipeline using Socrata API access, we recommend using this dataset if you'd like your boundaries to remain static. If you would like the boundaries to automatically update after each decennial census to reflect the most recent Supervisor District boundaries, see the Current Supervisor Districts dataset or the Current Supervisor Districts (trimmed to remove water and other non-populated City territories) dataset. E. RELATED DATASETS Supervisor Districts (2012) Current Supervisor Districts Current Supervisor Districts (trimmed to remove water and non-populated areas)

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Dwelling

UNITS IDENTIFIED: - Dwellings: Yes - Vacant units: Available but not included in current microdata version - Households: Yes - Individuals: Yes - Group quarters: Available but not included in current microdata version - Special populations: Not defined

UNIT DESCRIPTIONS: - Dwellings: Independent and separate space with areas of exclusive use, inhabited or designed to be inhabited by one or more persons. - Households: A person or group of people, related or not, who occupy all or part of a dwelling; attend to basic needs charged to a common budget, and they generally share food. - Group quarters: An institution in which a group of people generally not related lives and sleeps; done for reasons of study, work, religion, military discipline, administrative labors, rehabilitation, and others.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: DANE

SAMPLE UNIT: Dwelling

SAMPLE FRACTION: 10%

SAMPLE SIZE (person records): 4,117,607

Mode of data collection

Face-to-face [f2f]

Research instrument

Three enumeration questionnaires were used: 1. Questionnaire for the Urban environment. This is carried out by the field supervisor, through observation at the block level. It seeks to provide and overview of the predominant urban setting, based on criteria of habitat which are fundamentally physical. 2. Questionnaire of Census Units. This is carried out by the enumerator starting with the information reported directly by the units. It is divided into sections for: dwellings, households, persons, economic units and agricultural units. 3. Questionnaire for Special Housing Units (LEA). In the case of military barracks and penitentiary centers, this is carried out by resident personnel, trained for this purpose by the municipal coordinator. In the remaining cases, it is the responsibility of the enumerator.

Response rate

COVERAGE: 96.3%

Abstract

The main aim and objectives of the census is to provide benchmark statistics and a comprehensive profile of the population and households of Niue at a given time. This information obtained from the census is very crucial and useful in providing evidence to decision making and policy formulation for the Government, Business Community, Local Communities or Village Councils, Non Government Organisations of Niue and The International Communities who have an interest in Niue and its people.

Geographic coverage

National

Analysis unit

• Household
• Individual/Person
• Members Oversea

Universe

All households in Niue and all persons in the household including those temporarily overseas and those absent for not more than 12 months.

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionaire was published in English, a translated questionnaire was on hand when on demand by the respondent.

The questionnaire design differed slightly from the design of previous census questionnaires. As usual, government departments were asked to submit a list of questions on any specific topic they would like to add. Responses were not forthcoming in this census, although a few new questions were included.

There were two types of questionaires used in the census: the household questionaire and the individual questionnaire. An enumerator manual was prepared to assist the enumerators in their duties.

The questionnaire was pre-tested by the enumerators before they were to go out for field enumeration.

Cleaning operations

Census processing began as soon as questionaires were checked and coded. Forms were checked, edited and coded before being entered into the computer database.

Data processing was assisted by the Secretariat of the Pacific Community (SPC) using the computer software program CSPro for data entry and for generating tables. Tables were then exported to Excel for analysis.

Occupation and Industry were coded using the United Nations International Standard Classification of Occupation and International Standard Industrial Classification.

It is standard practice that as each area was completed the forms were first checked by the field supervisors for missing information and obvious inconsistencies. Omissions and errors identified at this stage were corrected by the enumerators.

The next stage was for the field supervisors to go through the completed forms again in the office to check in more detail for omissions and logical inconsistencies. Where they were found, the supervisors were responsible to take the necessary action.

Once the questionnaires had been thoroughly checked and edited, they were then coded in preparation for data processing.

Checking, editing and coding of the questionnaires in office were done after normal working hours as to ensure that the confidentiality of the survey is well observed.

A. SUMMARY This dataset contains a version of the current San Francisco Board of Supervisor district boundaries that have been trimmed to exclude non-populated City and County territory that is outside of the contiguous land mass of the City and County. This excludes for example City and County land in the Farallon Islands, Angel Island, and Alameda County, The underlying official current Supervisor District boundaries are available in the Current Supervisor Districts dataset. B. HOW THE DATASET IS CREATED This dataset will be updated to reflect the most current Supervisor District boundaries available. It currently reflects the same boundaries found in Supervisor Districts (2022). More information on how this was created can be found in the datasets by year: Supervisor Districts (2022) and Supervisor Districts (2012) C. UPDATE PROCESS Supervisor District boundaries are updated every 10 years following the federal decennial census. The Supervisor District boundaries reflected in this dataset will be manually updated after the next decennial census in 2030. The dataset is also manually updated as new members of the Board of Supervisors take office. The most recent manual update date is reflected in the 'data_as_of' field. D. HOW TO USE THIS DATASET This dataset can be joined to other datasets for analysis and reporting at the Supervisor District level. It is meant to facilitate visualization and mapping focussed on the contiguous land mass of the City & County and Treasure Island. If you are building an automated reporting pipeline using Socrata API access, we recommend using this dataset if you would like the boundaries to automatically update after each decennial census to reflect the most recent Supervisor District boundaries. If you'd like your boundaries to remain static, see the Supervisor Districts (2022) dataset. E. RELATED DATASETS Current Supervisor Districts Supervisor Districts (2022) Supervisor Districts (2012)

Population by age groups, race and gender, and the poverty by race is attached to the split tract geography to create this split tract with population and poverty data. Split tract data is the product of 2020 census tracts split by 2023 incorporated city boundaries and unincorporated community/countywide statistical areas (CSA) boundaries as of July 1, 2023. The census tract boundaries have been altered and aligned where necessary with legal city boundaries and unincorporated areas, including shoreline/coastal areas. Census Tract:Every 10 years the Census Bureau counts the population of the United States as mandated by Constitution. The Census Bureau (https://www.census.gov/)released 2020 geographic boundaries data including census tracts for the analysis and mapping of demographic information across the United States. City Boundary:City Boundary data is the base map information for the County of Los Angeles. These City Boundaries are based on the Los Angeles County Seamless Cadastral Landbase. The Landbase is jointly maintained by the Los Angeles County Assessor and the Los Angeles County Department of Public Works (DPW). This layer represents current city boundaries within Los Angeles County. The DPW provides the most current shapefiles representing city boundaries and city annexations. True, legal boundaries are only determined on the ground by surveyors licensed in the State of California.Countywide Statistical Areas (CSA): The countywide Statistical Area (CSA) was defined to provide a common geographic boundary for reporting departmental statistics for unincorporated areas and incorporated Los Angeles city to the Board of Supervisors. The CSA boundary and CSA names are established by the CIO and the LA County Enterprise GIS group worked with the Los Angeles County Board of Supervisors Unincorporated Area and Field Deputies that reflect as best as possible the general name preferences of residents and historical names of areas. This data is primarily focused on broad statistics and reporting, not mapping of communities. This data is not designed to perfectly represent communities, nor jurisdictional boundaries such as Angeles National Forest. CSA represent board approved geographies comprised of Census block groups split by cities.Data Fields:CT20: 2020 Census tractFIP22: 2023 City FIP CodeCITY: City name for incorporated cities and “Unincorporated” for unincorporated areas (as of July 1, 2023) CSA: Countywide Statistical Area (CSA) - Unincorporated area community names and LA City neighborhood names.CT20FIP23CSA: 2020 census tract with 2023 city FIPs for incorporated cities and unincorporated areas and LA neighborhoods. SPA22: 2022 Service Planning Area (SPA) number.SPA_NAME: Service Planning Area name.HD22: 2022 Health District (HD) number: HD_NAME: Health District name.POP23_AGE_0_4: 2023 population 0 to 4 years oldPOP23_AGE_5_9: 2023 population 5 to 9 years old POP23_AGE_10_14: 2023 population 10 to 14 years old POP23_AGE_15_17: 2022 population 15 to 17 years old POP23_AGE_18_19: 2023 population 18 to 19 years old POP23_AGE_20_44: 2023 population 20 to 24 years old POP23_AGE_25_29: 2023 population 25 to 29 years old POP23_AGE_30_34: 2023 population 30 to 34 years old POP23_AGE_35_44: 2023 population 35 to 44 years old POP23_AGE_45_54: 2023 population 45 to 54 years old POP23_AGE_55_64: 2023 population 55 to 64 years old POP23_AGE_65_74: 2023 population 65 to 74 years old POP23_AGE_75_84: 2023 population 75 to 84 years old POP23_AGE_85_100: 2023 population 85 years and older POP23_WHITE: 2023 Non-Hispanic White POP23_BLACK: 2023 Non-Hispanic African AmericanPOP23_AIAN: 2023 Non-Hispanic American Indian or Alaska NativePOP23_ASIAN: 2023 Non-Hispanic Asian POP23_HNPI: 2023 Non-Hispanic Hawaiian Native or Pacific IslanderPOP23_HISPANIC: 2023 HispanicPOP23_MALE: 2023 Male POP23_FEMALE: 2023 Female POV23_WHITE: 2023 Non-Hispanic White below 100% Federal Poverty Level POV23_BLACK: 2023 Non-Hispanic African American below 100% Federal Poverty Level POV23_AIAN: 2023 Non-Hispanic American Indian or Alaska Native below 100% Federal Poverty Level POV23_ASIAN: 2023 Non-Hispanic Asian below 100% Federal Poverty Level POV23_HNPI: 2023 Non-Hispanic Hawaiian Native or Pacific Islander below 100% Federal Poverty Level POV23_HISPANIC: 2023 Hispanic below 100% Federal Poverty Level POV23_TOTAL: 2023 Total population below 100% Federal Poverty Level POP23_TOTAL: 2023 Total PopulationAREA_SQMil: Area in square mile.POP23_DENSITY: 2023 Population per square mile.POV23_PERCENT: 2023 Poverty rate/percentage.How this data created?Population by age groups, ethnic groups and gender, and the poverty by ethnic groups is attributed to the split tract geography to create this data. Split tract polygon data is created by intersecting 2020 census tract polygons, LA Country City Boundary polygons and Countywide Statistical Areas (CSA) polygon data. The resulting polygon boundary aligned and matched with the legal city boundary whenever possible. Notes:1. Population and poverty data estimated as of July 1, 2023. 2. 2010 Census tract and 2020 census tracts are not the same. Similarly, city and community boundaries are as of July 1, 2023.

Tabular data of population by age groups, race and gender, and the poverty by race is attached to the split tract geography to create this split tract with population and poverty data. Split tract data is the product of 2020 census tracts split by 2020 incorporated city boundaries and unincorporated community/countywide statistical areas (CSA) boundaries. The census tract boundaries have been altered and aligned where necessary with legal city boundaries and unincorporated areas, including shoreline/coastal areas. Census Tract:Every 10 years the Census Bureau counts the population of the United States as mandated by Constitution. The Census Bureau (https://www.census.gov/) released 2020 geographic boundaries data including census tracts for the analysis and mapping of demographic information across the United States. City Boundary:City Boundary data is the base map information for the County of Los Angeles. These City Boundaries are based on the Los Angeles County Seamless Cadastral Landbase. The Landbase is jointly maintained by the Los Angeles County Assessor and the Los Angeles County Department of Public Works (DPW). This layer represents current city boundaries within Los Angeles County. The DPW provides the most current shapefiles representing city boundaries and city annexations. True, legal boundaries are only determined on the ground by surveyors licensed in the State of California.Countywide Statistical Areas (CSA): The countywide Statistical Area (CSA) was defined to provide a common geographic boundary for reporting departmental statistics for unincorporated areas and incorporated Los Angeles city to the Board of Supervisors. The CSA boundary and CSA names are established by the CIO and the LA County Enterprise GIS group worked with the Los Angeles County Board of Supervisors Unincorporated Area and Field Deputies that reflect as best as possible the general name preferences of residents and historical names of areas. This data is primarily focused on broad statistics and reporting, not mapping of communities. This data is not designed to perfectly represent communities, nor jurisdictional boundaries such as Angeles National Forest. CSA represent board approved geographies comprised of Census block groups split by cities.Data Field:CT20: 2020 Census tractFIP21: 2020 City FIP CodeCITY: City name for incorporated cities and “Unincorporated” for unincorporated areas (as of July 1, 2020) CSA: Countywide Statistical Area (CSA) - Unincorporated area community names and LA City neighborhood names.CT20FIP21CSA: 2020 census tract with 2020 city FIPs for incorporated cities, unincorporated areas and LA neighborhoods. SPA22: 2022 Service Planning Area (SPA) number.SPA_NAME: Service Planning Area name.HD22: 2022 Health District (HD) number: HD_NAME: Health District name.POP20_AGE_0_4: 2020 population 0 to 4 years oldPOP20_AGE_5_9: 2020 population 5 to 9 years old POP20_AGE_10_14: 2020 population 10 to 14 years old POP20_AGE_15_17: 2020 population 15 to 17 years old POP20_AGE_18_19: 2020 population 18 to 19 years old POP20_AGE_20_44: 2020 population 20 to 24 years old POP20_AGE_25_29: 2020 population 25 to 29 years old POP20_AGE_30_34: 2020 population 30 to 34 years old POP20_AGE_35_44: 2020 population 35 to 44 years old POP20_AGE_45_54: 2020 population 45 to 54 years old POP20_AGE_55_64: 2020 population 55 to 64 years old POP20_AGE_65_74: 2020 population 65 to 74 years old POP20_AGE_75_84: 2020 population 75 to 84 years old POP20_AGE_85_100: 2020 population 85 years and older POP20_WHITE: 2020 Non-Hispanic White POP20_BLACK: 2020 Non-Hispanic African AmericanPOP20_AIAN: 2020 Non-Hispanic American Indian or Alaska NativePOP20_ASIAN: 2020 Non-Hispanic Asian POP20_HNPI: 2020 Non-Hispanic Hawaiian Native or Pacific IslanderPOP20_HISPANIC: 2020 HispanicPOP20_MALE: 2020 Male POP20_FEMALE: 2020 Female POV20_WHITE: 2020 Non-Hispanic White below 100% Federal Poverty Level POV20_BLACK: 2020 Non-Hispanic African American below 100% Federal Poverty Level POV20_AIAN: 2020 Non-Hispanic American Indian or Alaska Native below 100% Federal Poverty Level POV20_ASIAN: 2020 Non-Hispanic Asian below 100% Federal Poverty Level POV20_HNPI: 2020 Non-Hispanic Hawaiian Native or Pacific Islander below 100% Federal Poverty Level POV20_HISPANIC: 2020 Hispanic below 100% Federal Poverty Level POV20_TOTAL: 2020 Total population below 100% Federal Poverty Level POP20_TOTAL: 2020 Total PopulationAREA_SQMIL: Area in square milePOP20_DENSITY: Population per square mile.POV20_PERCENT: Poverty rate/percentage.How this data created?The tabular data of population by age groups, by ethnic groups and by gender, and the poverty by ethnic groups is attributed to the split tract geography to create this data. Split tract polygon data is created by intersecting 2020 census tract polygons, LA Country City Boundary polygons and Countywide Statistical Areas (CSA) polygon data. The resulting polygon boundary aligned and matched with the legal city boundary whenever possible. Note:1. Population and poverty data estimated as of July 1, 2019.2. 2010 Census tract and 2020 census tracts are not the same. Similarly, city and community boundary are not the same because boundary is reviewed and updated annually.

Tabular data of population by age groups, race and gender, and the poverty by race is attached to the split tract geography to create this split tract with population and poverty data. Split tract data is the product of 2010 census tracts split by 2016 incorporated city boundaries and unincorporated community/countywide statistical areas (CSA) boundaries. The census tract boundaries have been altered and aligned where necessary with legal city boundaries and unincorporated areas, including shoreline/coastal areas. Census Tract:Every 10 years the Census Bureau counts the population of the United States as mandated by Constitution. The Census Bureau (https://www.census.gov/) released 2010 geographic boundaries data including census tracts for the analysis and mapping of demographic information across the United States. City Boundary:City Boundary data is the base map information for the County of Los Angeles. These City Boundaries are based on the Los Angeles County Seamless Cadastral Landbase. The Landbase is jointly maintained by the Los Angeles County Assessor and the Los Angeles County Department of Public Works (DPW). This layer represents current city boundaries within Los Angeles County. The DPW provides the most current shapefiles representing city boundaries and city annexations. True, legal boundaries are only determined on the ground by surveyors licensed in the State of California.Countywide Statistical Areas (CSA): The countywide Statistical Area (CSA) was defined to provide a common geographic boundary for reporting departmental statistics for unincorporated areas and incorporated Los Angeles city to the Board of Supervisors. The CSA boundary and CSA names are established by the CIO and the LA County Enterprise GIS group worked with the Los Angeles County Board of Supervisors Unincorporated Area and Field Deputies that reflect as best as possible the general name preferences of residents and historical names of areas. This data is primarily focused on broad statistics and reporting, not mapping of communities. This data is not designed to perfectly represent communities, nor jurisdictional boundaries such as Angeles National Forest. CSA represent board approved geographies comprised of Census block groups split by cities.Data Field:CT10: 2010 Census tractFIP16: 2016 City FIP CodeCITY: City name for incorporated cities and “Unincorporated” for unincorporated areas (as of July 1, 2016) CSA: Countywide Statistical Area (CSA) - Unincorporated area community names and LA City neighborhood names.CT10FIP16CSA: 2010 census tract with 2016 city FIPs for incorporated cities, unincorporated areas and LA neighborhoods. SPA12: 2012 Service Planning Area (SPA) number.SPA_NAME: Service Planning Area name.HD12: 2012 Health District (HD) number: HD_NAME: Health District name.POP16_AGE_0_4: 2016 population 0 to 4 years oldPOP16_AGE_5_9: 2016 population 5 to 9 years old POP16_AGE_10_14: 2016 population 10 to 14 years old POP16_AGE_15_17: 2016 population 15 to 17 years old POP16_AGE_18_19: 2016 population 18 to 19 years old POP16_AGE_20_44: 2016 population 20 to 24 years old POP16_AGE_25_29: 2016 population 25 to 29 years old POP16_AGE_30_34: 2016 population 30 to 34 years old POP16_AGE_35_44: 2016 population 35 to 44 years old POP16_AGE_45_54: 2016 population 45 to 54 years old POP16_AGE_55_64: 2016 population 55 to 64 years old POP16_AGE_65_74: 2016 population 65 to 74 years old POP16_AGE_75_84: 2016 population 75 to 84 years old POP16_AGE_85_100: 2016 population 85 years and older POP16_WHITE: 2016 Non-Hispanic White POP16_BLACK: 2016 Non-Hispanic African AmericanPOP16_AIAN: 2016 Non-Hispanic American Indian or Alaska NativePOP16_ASIAN: 2016 Non-Hispanic Asian POP16_HNPI: 2016 Non-Hispanic Hawaiian Native or Pacific IslanderPOP16_HISPANIC: 2016 HispanicPOP16_MALE: 2016 Male POP16_FEMALE: 2016 Female POV16_WHITE: 2016 Non-Hispanic White below 100% Federal Poverty Level POV16_BLACK: 2016 Non-Hispanic African American below 100% Federal Poverty Level POV16_AIAN: 2016 Non-Hispanic American Indian or Alaska Native below 100% Federal Poverty Level POV16_ASIAN: 2016 Non-Hispanic Asian below 100% Federal Poverty Level POV16_HNPI: 2016 Non-Hispanic Hawaiian Native or Pacific Islander below 100% Federal Poverty Level POV16_HISPANIC: 2016 Hispanic below 100% Federal Poverty Level POV16_TOTAL: 2016 Total population below 100% Federal Poverty Level POP16_TOTAL: 2016 Total PopulationAREA_SQMIL: Area in square milePOP16_DENSITY: Population per square mile.POV16_PERCENT: Poverty rate/percentage.How this data created?The tabular data of population by age groups, by ethnic groups and by gender, and the poverty by ethnic groups is attributed to the split tract geography to create this data. Split tract polygon data is created by intersecting 2010 census tract polygons, LA Country City Boundary polygons and Countywide Statistical Areas (CSA) polygon data. The resulting polygon boundary aligned and matched with the legal city boundary whenever possible. Note:1. Population and poverty data estimated as of July 1, 2016. 2. 2010 Census tract and 2020 census tracts are not the same. Similarly, city and community boundary are not the same because boundary is reviewed and updated annually.

Tabular data of population by age groups, race and gender, and the poverty by race is attached to the split tract geography to create this split tract with population and poverty data. Split tract data is the product of 2010 census tracts split by 2014 incorporated city boundaries and unincorporated community/countywide statistical areas (CSA) boundaries. The census tract boundaries have been altered and aligned where necessary with legal city boundaries and unincorporated areas, including shoreline/coastal areas. Census Tract:Every 10 years the Census Bureau counts the population of the United States as mandated by Constitution. The Census Bureau (https://www.census.gov/) released 2010 geographic boundaries data including census tracts for the analysis and mapping of demographic information across the United States. City Boundary:City Boundary data is the base map information for the County of Los Angeles. These City Boundaries are based on the Los Angeles County Seamless Cadastral Landbase. The Landbase is jointly maintained by the Los Angeles County Assessor and the Los Angeles County Department of Public Works (DPW). This layer represents current city boundaries within Los Angeles County. The DPW provides the most current shapefiles representing city boundaries and city annexations. True, legal boundaries are only determined on the ground by surveyors licensed in the State of California.Countywide Statistical Areas (CSA): The countywide Statistical Area (CSA) was defined to provide a common geographic boundary for reporting departmental statistics for unincorporated areas and incorporated Los Angeles city to the Board of Supervisors. The CSA boundary and CSA names are established by the CIO and the LA County Enterprise GIS group worked with the Los Angeles County Board of Supervisors Unincorporated Area and Field Deputies that reflect as best as possible the general name preferences of residents and historical names of areas. This data is primarily focused on broad statistics and reporting, not mapping of communities. This data is not designed to perfectly represent communities, nor jurisdictional boundaries such as Angeles National Forest. CSA represent board approved geographies comprised of Census block groups split by cities.Data Field:CT10: 2010 Census tractFIP14: 2014 City FIP CodeCITY: City name for incorporated cities and “Unincorporated” for unincorporated areas (as of July 1, 2014) CT10FIP14: 2010 census tract with 2014 city FIPs for incorporated cities and unincorporated areas. SPA12: 2012 Service Planning Area (SPA) number.SPA_NAME: Service Planning Area name.HD12: 2012 Health District (HD) number: HD_NAME: Health District name.POP14_AGE_0_4: 2014 population 0 to 4 years oldPOP14_AGE_5_9: 2014 population 5 to 9 years old POP14_AGE_10_14: 2014 population 10 to 14 years old POP14_AGE_15_17: 2014 population 15 to 17 years old POP14_AGE_18_19: 2014 population 18 to 19 years old POP14_AGE_20_44: 2014 population 20 to 24 years old POP14_AGE_25_29: 2014 population 25 to 29 years old POP14_AGE_30_34: 2014 population 30 to 34 years old POP14_AGE_35_44: 2014 population 35 to 44 years old POP14_AGE_45_54: 2014 population 45 to 54 years old POP14_AGE_55_64: 2014 population 55 to 64 years old POP14_AGE_65_74: 2014 population 65 to 74 years old POP14_AGE_75_84: 2014 population 75 to 84 years old POP14_AGE_85_100: 2014 population 85 years and older POP14_WHITE: 2014 Non-Hispanic White POP14_BLACK: 2014 Non-Hispanic African AmericanPOP14_AIAN: 2014 Non-Hispanic American Indian or Alaska NativePOP14_ASIAN: 2014 Non-Hispanic Asian POP14_HNPI: 2014 Non-Hispanic Hawaiian Native or Pacific IslanderPOP14_HISPANIC: 2014 HispanicPOP14_MALE: 2014 Male POP14_FEMALE: 2014 Female POV14_WHITE: 2014 Non-Hispanic White below 100% Federal Poverty Level POV14_BLACK: 2014 Non-Hispanic African American below 100% Federal Poverty Level POV14_AIAN: 2014 Non-Hispanic American Indian or Alaska Native below 100% Federal Poverty Level POV14_ASIAN: 2014 Non-Hispanic Asian below 100% Federal Poverty Level POV14_HNPI: 2014 Non-Hispanic Hawaiian Native or Pacific Islander below 100% Federal Poverty Level POV14_HISPANIC: 2014 Hispanic below 100% Federal Poverty Level POV14_TOTAL: 2014 Total population below 100% Federal Poverty Level POP14_TOTAL: 2014 Total PopulationAREA_SQMIL: Area in square milePOP14_DENSITY: Population per square mile.POV14_PERCENT: Poverty rate/percentage.How this data created?The tabular data of population by age groups, by ethnic groups and by gender, and the poverty by ethnic groups is attributed to the split tract geography to create this data. Split tract polygon data is created by intersecting 2010 census tract polygons, LA Country City Boundary polygons and Countywide Statistical Areas (CSA) polygon data. The resulting polygon boundary aligned and matched with the legal city boundary whenever possible. Note:1. Population and poverty data estimated as of July 1, 2014. 2. 2010 Census tract and 2020 census tracts are not the same. Similarly, city and community boundary are not the same because boundary is reviewed and updated annually.

Tabular data of population by age groups, race and gender, and the poverty by race is attached to the split tract geography to create this split tract with population and poverty data. Split tract data is the product of 2010 census tracts split by 2012 incorporated city boundaries and unincorporated community/countywide statistical areas (CSA) boundaries. The census tract boundaries have been altered and aligned where necessary with legal city boundaries and unincorporated areas, including shoreline/coastal areas. Census Tract:Every 10 years the Census Bureau counts the population of the United States as mandated by Constitution. The Census Bureau (https://www.census.gov/) released 2010 geographic boundaries data including census tracts for the analysis and mapping of demographic information across the United States. City Boundary:City Boundary data is the base map information for the County of Los Angeles. These City Boundaries are based on the Los Angeles County Seamless Cadastral Landbase. The Landbase is jointly maintained by the Los Angeles County Assessor and the Los Angeles County Department of Public Works (DPW). This layer represents current city boundaries within Los Angeles County. The DPW provides the most current shapefiles representing city boundaries and city annexations. True, legal boundaries are only determined on the ground by surveyors licensed in the State of California.Countywide Statistical Areas (CSA): The countywide Statistical Area (CSA) was defined to provide a common geographic boundary for reporting departmental statistics for unincorporated areas and incorporated Los Angeles city to the Board of Supervisors. The CSA boundary and CSA names are established by the CIO and the LA County Enterprise GIS group worked with the Los Angeles County Board of Supervisors Unincorporated Area and Field Deputies that reflect as best as possible the general name preferences of residents and historical names of areas. This data is primarily focused on broad statistics and reporting, not mapping of communities. This data is not designed to perfectly represent communities, nor jurisdictional boundaries such as Angeles National Forest. CSA represent board approved geographies comprised of Census block groups split by cities.Data Field:CT10: 2010 Census tractFIP12: 2012 City FIP CodeCITY: City name for incorporated cities and “Unincorporated” for unincorporated areas (as of July 1, 2012) CT10FIP12: 2010 census tract with 2012 city FIPs for incorporated cities and unincorporated areas. SPA12: 2012 Service Planning Area (SPA) number.SPA_NAME: Service Planning Area name.HD12: 2012 Health District (HD) number: HD_NAME: Health District name.POP12_AGE_0_4: 2012 population 0 to 4 years oldPOP12_AGE_5_9: 2012 population 5 to 9 years old POP12_AGE_10_14: 2012 population 10 to 14 years old POP12_AGE_15_17: 2012 population 15 to 17 years old POP12_AGE_18_19: 2012 population 18 to 19 years old POP12_AGE_20_44: 2012 population 20 to 24 years old POP12_AGE_25_29: 2012 population 25 to 29 years old POP12_AGE_30_34: 2012 population 30 to 34 years old POP12_AGE_35_44: 2012 population 35 to 44 years old POP12_AGE_45_54: 2012 population 45 to 54 years old POP12_AGE_55_64: 2012 population 55 to 64 years old POP12_AGE_65_74: 2012 population 65 to 74 years old POP12_AGE_75_84: 2012 population 75 to 84 years old POP12_AGE_85_100: 2012 population 85 years and older POP12_WHITE: 2012 Non-Hispanic White POP12_BLACK: 2012 Non-Hispanic African AmericanPOP12_AIAN: 2012 Non-Hispanic American Indian or Alaska NativePOP12_ASIAN: 2012 Non-Hispanic Asian POP12_HNPI: 2012 Non-Hispanic Hawaiian Native or Pacific IslanderPOP12_HISPANIC: 2012 HispanicPOP12_MALE: 2012 Male POP12_FEMALE: 2012 Female POV12_WHITE: 2012 Non-Hispanic White below 100% Federal Poverty Level POV12_BLACK: 2012 Non-Hispanic African American below 100% Federal Poverty Level POV12_AIAN: 2012 Non-Hispanic American Indian or Alaska Native below 100% Federal Poverty Level POV12_ASIAN: 2012 Non-Hispanic Asian below 100% Federal Poverty Level POV12_HNPI: 2012 Non-Hispanic Hawaiian Native or Pacific Islander below 100% Federal Poverty Level POV12_HISPANIC: 2012 Hispanic below 100% Federal Poverty Level POV12_TOTAL: 2012 Total population below 100% Federal Poverty Level POP12_TOTAL: 2012 Total PopulationAREA_SQMIL: Area in square milePOP12_DENSITY: Population per square mile.POV12_PERCENT: Poverty rate/percentage.How this data created?The tabular data of population by age groups, by ethnic groups and by gender, and the poverty by ethnic groups is attributed to the split tract geography to create this data. Split tract polygon data is created by intersecting 2010 census tract polygons, LA Country City Boundary polygons and Countywide Statistical Areas (CSA) polygon data. The resulting polygon boundary aligned and matched with the legal city boundary whenever possible. Note:1. Population and poverty data estimated as of July 1, 2012. 2. 2010 Census tract and 2020 census tracts are not the same. Similarly, city and community boundary are not the same because boundary is reviewed and updated annually.

Abstract

The ancient history of Nepal is assumed to have begun in 750 B.C. and ended in 250 A.D. During that period Kirats ruled the country. But no written record of this is available. Early history of Nepal had witnessed the establishment of a number of beleaguered dynasties and principalities scattered in the fertile valleys of Kathmandu and Pokhara and in the river basins of the Karnali and the Gandaki. Although some others dynasties survived for a short period of time, others ruled for centuries. The Lichhavi dynasty, for instance, lasted over four centuries (464-879 A.D.). Another great dynasty-the Malla-Dynasty-had established itself in Kathmandu valley around the 13th century, and lasted over five hundred years.The divided and hostile principalities and kingdoms were finally consolidated in 1769 under king Prithivi Narayan Shah and his successors to become the modern nation of Nepal. Socially and economically, however, the modern era in Nepal's history has started with the revival of the national aspirations of the poor countries in Asia after the Second World War. These aspirations were mainly concerned with acquiring independence, and emancipation from the perpetual state of ignorance, poverty and political stress. Failing to democratize the regime and to bring about educational, social and economic reforms in the country, the Rana Regime was finally thrown out by the joint efforts of the King and people of Nepal in 1951. Within the frame of the open policy with other nations, Nepal has been able to implement four economic development plans, with the cooperation of several countries and International Agencies. The fifth economic development plan (1975-80) has placed special priority on agricultural development as infrastructure for future industrial development and also has laid emphasis on industrialization of the country than the previous plans.

The objectives of the 1981 Population Census were:

1. to provide data for small administrative areas of the country on population, housing and household facilities,
2. to provide sex disaggregated data of the population and other variables related to households, demographic, social and economic conditions of the country, and
3. to provide detailed information on women, children, the aged and the disabled.
4. to determine the prevailing trends and characteristics of population change, namely, age structure, mortality, fertility, education and labour force.

The 1981 census contained the following items as the content of the census;

Individual Questionnaire Name of the family members, Relation with household head, Sex, Age, Birth place, Citizenship, Mother tongue, Religion, Educational attainment, Marital Status, Economic activities, Profession

Household Questionnaire Name of the household head, Number of present members of the households- total, male, female, Number of absentee members of the households- total, male, female, Place of absentee and reason of leaving, Number of deaths in the households in the past 12 months-male and female, Physical and mental disabilities, Number of radios in the households, Economic activities (agriculture and cottage industries).

Geographic coverage

National

Analysis unit

Individual, household

Universe

The census covered all de jure household members (usual residents) in private households.

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

The census questionnaire is the ultimate field document from which all data are compiled. Needless to say that the simpler is the questionnaire designed the greater will be the level of accuracy and easier the counting procedures and coding and editing of the items. The questionnaire used in 1981 census was pre-coded. The purpose of pre-coding was initially to minimize the answers to be written so that further editing and coding processes would also be minimized.

Individual Questionnaire The individual characteristics questionnaire was more comprehensive in 1981 than in 1971.The items asked in individual schedule in 1981 census are:

1. Zone
2. District
3. Urban/Village Panchyat
4. Ward no.
5. House no.
6. Households serial number
7. Enumerators name
8. Enumeration date
9. Supervisor`s name and signature
10. Name of the family members
11. Relation with household head
12. Sex
13. Age
14. Birth place
15. Citizenship
16. Mother tongue
17. Religion
18. Educational attainment
19. Marital Status
20. Economic activities
21. Profession

Household Questionnaire The household characteristics questionnaire was also more comprehensive in 1981 than in 1971.The items asked in household schedule in 1981 census are, 1. Zone 2. District 3. Urban/Village Panchyat 4. Ward no. 5. House no. 6. Households serial number 7. Enumerators name 8. Enumeration date 9. Supervisor`s name and signature 10. Name of the household head 11. Number of present members of the households- total, male, female 12. Number of absentee members of the households- total, male, female 13. Place of absentee and reason of leaving 14. Number of deaths in the households in the past 12 months-male and female 15. Physical and mental disabilities 16. Number of radios in the households 17. Economic activities (agriculture and cottage industries) 18. Signature of the respondents

In order to simplify the job of editing and coding many of the items both in household and individual schedules were preceded. But there are some unavoidable problems with preceded answers. First, they make the questionnaires too long and unwieldy. This has what exactly happened with the 1981 questionnaires. One questionnaire is 21" long and 15.5" wide which is certainly too clumsy to carry around and complete. Secondly, in pre-coded questions the respondent is given a limited number of answers from which to choose which can often conceal information. Finally, once a tick has been put on the preceded answer there would be no way to check whether the interviewer did it correctly or not. It is, of course, necessary to have some answers preceded such as, “yes” or “No” type answers and some multiple choice responses but not at the cost of limiting response categories.

Cleaning operations

A primary check on major inconsistencies was done by the field supervisors on the spot in order to tally the household schedule with the census questionnaire. The completed schedules were then returned to the headquarters from the field where further editing and coding procedures were completed by the supervisors. It was expected that a considerable proportion of unknown category will come about particularly regarding age, economic status, and other items. Regarding age some method was elaborated in pointing out a direct relationship between age and certain major events occurring during the last six or seven decades from which the enumerator, if the respondent fails to estimate his age, could deduce the respondent 's approximate age. It was thought that this method would ultimately give a better estimate of ages, instead of obtaining a very big category of unknown ages. Admittedly, this procedure had, to some extent given the enumerator, the liberty to estimate the respondent's age within the limits of a wide range, particularly, adult ages. The edited schedules were then sent for coding operation. For coding 20 supervisors and 200 coders were employed. The job was completed in less than 9 months.

The purpose of the Project on Policing Neighborhoods (POPN) was to provide an in-depth description of how the police and the community interact with each other in a community policing (CP) environment. Research was conducted in Indianapolis, Indiana, in 1996 and in St. Petersburg, Florida, in 1997. Several research methods were employed: systematic observation of patrol officers (Parts 1-4) and patrol supervisors (Parts 5-14), in-person interviews with patrol officers (Part 15) and supervisors (Parts 16-17), and telephone surveys of residents in selected neighborhoods (Part 18). Field researchers accompanied their assigned patrol or supervising officer during all activities and encounters with the public during the shift. Field researchers noted when various activities and encounters with the public occurred during these "ride-alongs," who was involved, and what happened. In the resulting data files coded observation data are provided at the ride level, the activity level (actions that did not involve interactions with citizens), the encounter level (events in which officers interacted with citizens), and the citizen level. In addition to encounters with citizens, supervisors also engaged in encounters with patrol officers. Patrol officers and patrol supervisors in both Indianapolis and St. Petersburg were interviewed one-on-one in a private interviewing room during their regular work shifts. Citizens in the POPN study beats were randomly selected for telephone surveys to determine their views about problems in their neighborhoods and other community issues. Administrative records were used to create site identification data (Part 19) and data on staffing (Part 20). This data collection also includes data compiled from census records, aggregated to the beat level for each site (Part 21). Census data were also used to produce district populations for both sites (Part 22). Citizen data were aggregated to the encounter level to produce counts of various citizen role categories and characteristics and characteristics of the encounter between the patrol officer and citizens in the various encounters (Part 23). Ride-level data (Parts 1, 5, and 10) contain information about characteristics of the ride, including start and end times, officer identification, type of unit, and beat assignment. Activity data (Parts 2, 6, and 11) include type of activity, where and when the activity took place, who was present, and how the officer was notified. Encounter data (Parts 3, 7, and 12) contain descriptive information on encounters similar to the activity data (i.e., location, initiation of encounter). Citizen data (Parts 4, 8, and 13) provide citizen characteristics, citizen behavior, and police behavior toward citizens. Similarly, officer data from the supervisor observations (Parts 9 and 14) include characteristics of the supervising officer and the nature of the interaction between the officers. Both the patrol officer and supervisor interview data (Parts 15-17) include the officers' demographics, training and knowledge, experience, perceptions of their beats and organizational environment, and beliefs about the police role. The patrol officer data also provide the officers' perceptions of their supervisors while the supervisor data describe supervisors' perceptions of their subordinates, as well as their views about their roles, power, and priorities as supervisors. Data from surveyed citizens (Part 18) provide information about their neighborhoods, including years in the neighborhood, distance to various places in the neighborhood, neighborhood problems and effectiveness of police response to those problems, citizen knowledge of, or interactions with, the police, satisfaction with police services, and friends and relatives in the neighborhood. Citizen demographics and geographic and weight variables are also included. Site identification variables (Part 19) include ride and encounter numbers, site beat (site, district, and beat or community policing areas [CPA]), and sector. Staffing variables (Part 20) include district, shift, and staffing levels for various shifts. Census data (Part 21) include neighborhood, index of socioeconomic distress, total population, and total white population. District population variables (Part 22) include district and population of district. The aggregated citizen data (Part 23) provide the ride and encounter numbers, number of citizens in the encounter, counts of citizens by their various roles, and by sex, age, race, wealth, if known by the police, under the influence of alcohol or drugs, physically injured, had a weapon, or assaulted the police, counts by type of encounter, and counts of police and citizen actions during the encounter.

Abstract

The 2011 Population and Housing Census of Samoa was taken on the midnight of November the 7th 2011. It counted every person in the country on that night and collected a wide range of social, economic and demographic information about each individual and their housing status.

The information were used to develop statistical indicators to support national plannning and policy-making and also to monitor MDG indicators and all other related conventions. This included population growth rates, educational attainment, employment rates, fertility rates, mortality rates, internal movements, household access to water supply, electricity, sanitation, and many other information. The full report is available at SBS website: http://www.sbs.gov.ws under the section on Population statistics and demography.

Geographic coverage

National coverage Regions Districts Village Enumeration areas

Analysis unit

Private households Institutional households Individuals Women 15-49 Housing/Buildings

Universe

The PHC 2011 covered all de facto household members, institutional households such as boarding schools, hospitals, prison inmates and expatriates residing in Samoa for more than 3 months. The PHC excluded all tourists visiting Samoa during the enumeration period and all Samoans residing overseas.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Not applicable to a complete enumeration census.

Mode of data collection

Face-to-face [f2f]

Research instrument

Users' consultation seminars were conducted for three consecutive days (June 8th -10th, 2010) with financial support provided by the office of UNFPA in Suva via the Samoa Parliamentary Group for Population Development (SPGPD) annual programs. For the first time in census history, the SPGPD or members of parliament have become the target group of users to get involved in any census questionnaire consultations.

All government ministries and non-governmental organizations were invited to the consultation seminars and each was asked to make a presentation of data needs for consideration in the final census 2011 questionnaire. To avoid re-inventing the wheel in the compilation of the list of census questions for census 2011, the questionnaire from the census 2006 was reprinted and distributed to all participants and presenters to select questions that they would consider again for the census 2011 in addition to their new data needs. Users were also advised that any new question would need good justifications of how it links to national interests.

At the end of the three days seminar, all new questions were compiled for final selection by Samoa Bureau of Statistics. Not all the users' data needs have been included in the final 2011 census questionnaire due mainly to the cost involved and limited time for census enumeration. Therefore, the final selection of questions was purely based on the linkage of the data being requested to the list of statistical indicators in the 'Strategy for the Development of Samoa 2008-2012' (SDS) and the 'Millennium Development Goals' (MDGs) 2015. All data requests outside of the two frameworks were put aside to be integrated in other more appropriate survey activities by the bureau.

From July 2010-December 2010, the questionnaire was formatted using the In-Design CS4 software. It is important to note that the PHC 2011 was the first ever census using the scanning technology to process data from the census questionnaires as a replacement of the usual manual data entry process. The scanning was pilot tested in April 2011, before it was finally used for final census enumeration.

The questionnaire was designed using A3 paper size.

The Population questionnaire was administered in each household, which collected various information on household members including age, sex, citizenship, disability, orphanhood, marital status, residence (birth, usual, previous), religion, education and employment.

In the Population questionnaire, a special section was administered in each household for women age 15-49, which also asked information on their children ever born still living, died or living somewhere else. Mothers of children under one year were also asked whether their last born children were still living at the time of the census.

The Housing questionnaire was also administered in each household which collected information on the types of building the household lived, floor materials, wall materials, roof materials, land tenure, house tenure, water supply, drinking water, lighting, cooking fuel, toilet facility, telephone, computer, internet, refrigerator, radio, television and others.

Cleaning operations

Data editing was done in several stages. 1. Office manual editing and coding 2. Automatic scanning data entry edits 3. Visual verification questionnaire edits 3. Structure checking and completeness 4. Structure checks of the CSPro data files Editing program can be enquired at the Division of IT and Data Processing at email address: info.stats@sbs.gov.ws

Sampling error estimates

The census is a full-coverage of the population, therefore it is not a sample where sampling errors can be estimated.

Data appraisal

There was no post-enumeration in the census 2011. One of the normal practices by the bureau to validate the total population counts from all villages, districts and regions of Samoa in any census is the manual count of the population in all areas during the on-going census enumeration.That information is collected by the enumerators and field supervisors during the enumeration using the Enumerators and Supervisors control forms. At the end of the enumeration, the control forms which mainly contained the number of males and females per enumeration area will be collected and compiled by the Census and Survey division as the first preliminary count of the census. In the census 2011, the preliminary population counts were compiled and launched as the 'Village Directory 2011' report after 4 weeks from end of the enumeration period.

The significance of the Village Directory report is it helps to provide a qiuick overall picture of the population growth and population distribution in all villages of the country relative to previous censuses. Most important of all is that the preliminary count will provide the basis for a decision whether a post-enumeration is warrant or otherwise. If the preliminary country is close to the projected population then the post-enumeration is assumed not worth the cost because it is expensive and it will delay all other census processes. In the census 2011, the preliminary count arrived at 186,340 which was more than the projected population of 184,032 as depicted in the Statistical Abstract 2009. Therefore the decision was made that post-enumeration was not worth it.

Abstract

Geostat conducted Census of Agriculture 2014 in accordance with the World Programme of Agricultural Censuses 2006-2015 recommended by the Food and Agriculture Organization (FAO). The census was based on the FAO methodology. Statistics experts of FAO and the United States Department of Agriculture (USDA) were actively engaged at every stage of the census process. At the first stage, in November 2014, together with Population Census there was conducted Census of Agriculture for households. In addition to this, in spring 2015 there was conducted Census of Agriculture for legal entities. As a result, the census covered all agricultural holdings in the country (on the territory controlled by the Government of Georgia) – all households and legal entities, who, as of October 1, 2014, were owning or temporarily operating agricultural land, livestock, poultry, beehive or permanent crop (agricultural), regardless the fact whether there was produced any kind of agricultural product or not during the reference year. The census provided diverse information about agriculture of Georgia such is structure and use of land operated by holdings, livestock, poultry and beehive numbers.

Geographic coverage

National coverage

Analysis unit

Households

Universe

The main statistical unit was the agricultural holding, defined as an economic unit engaged in agricultural production under single management without regard to size and legal status. An economic unit that operates agricultural land or permanent crop trees, but that during the reference year has no agricultural production, is also considered an agricultural holding. As the AC 2014 data collection for the agricultural holdings in the household sector was carried out jointly with the GPC, the common statistical unit was the agricultural production household. Two types of agricultural holdings were distinguished: family holdings and agricultural enterprises.

Kind of data

Census/enumeration data [cen]

Sampling procedure

(a) Frame In 2013, Geostat conducted preliminary fieldwork to establish the list of dwellings and households existing in Georgia. The information received from the preliminary fieldwork was used to update and finalize the census frame for data collection. For agricultural enterprises, to ensure full coverage of the list of potential agricultural enterprises, all existing reliable sources in the country were used.

Mode of data collection

Face-to-face [f2f]

Research instrument

One questionnaire was used for the AC 2014 data collection, in both paper and electronic format covering:

• Household roster
• Number of Holdings
• Structure of the Land Operated by Holdings
• Agricultural Land and Its Use
• Arable Land
• Permanent Crops
• Orchards
• Vineyards
• Livestock and Poultry

The AC 2014 questionnaire covered 15 of the 16 core items recommended for the WCA 2010 round. The following item was not covered: "Other economic production activities of the holding's enterprise".

Cleaning operations

(a) DATA PROCESSING AND ARCHIVING For several months after the census enumeration, approximately 300 people worked on the digitalization of census data. They were permanently supervised by IT and other technical staff. In parallel, digitized questionnaires were compared with paper questionnaires by editors. Finally, data were cleaned by the appropriate division at the central office of Geostat. The data cleaning process used several methods. Data relating to large holdings were verified by telephone calls. In addition, different reliable sources (registers) were used to fill in missing data. Furthermore, donor imputation was used to fill in the missing values. For tabulation, a special software was prepared by Geostat. Geostat implemented a microdata archiving system to save the census data.

(b) CENSUS DATA QUALITY Geostat conducted a PES to assess the quality of the AC. During the fieldwork, Geostat used a six-level control system, which involved the following categories of census staff: field work coordinator, regional coordinator, municipal supervisor, sector supervisor, instructor-coordinator and enumerator.

Abstract

This was the second Agricultural Census to be conducted in Niue since the last one in 1989. As well as collecting information on agriculture, the census also included some detail information on the population to provide the Government with up-to-date information on some important population parameters. Although this as only the second agricultural census to be conducted in Niue, the country has a long history of Population activities and has gained experiences in data collection. Nevertheless, Food and Agricultural Organization of the United Nations (FAO) provided technical assistance under TCP/Niue/3101 through the services of an Agricultural Census Expert and a Data Processing Expert.

Geographic coverage

National coverage

Analysis unit

Households

Universe

The statistical unit was the agricultural holding, defined as an economic unit of agricultural production under single management, comprising all livestock kept and all land used wholly or partly for agricultural production purposes, without regard to title, legal form or size. According to legal status, the holdings were classified as: (i) individual household on own account; (ii) in partnership; (iii) a village association; or (iv) institution.

Kind of data

Census/enumeration data [cen]

Sampling procedure

a. The Enumeration The country was divided to 21 Enumeration Areas (EAs) for the enumeration purposes. This division was based on the Population and Household Census 2006. There were 30 EAs in the first Agriculture Census in 1989 and the decline of number of EAs to 21 this time was the direct result of the declining population and number of households.

Mode of data collection

Face-to-face [f2f]

Research instrument

Altogether, three questionnaires were used:

1 Household Form 2 Holding Form 3 Parcel Form.

The following information was required from all households:

(i) Location of household (ii) Date of birth, sex, Age, Decent, Country of Residence for all persons (iii) Educational Attainment, Main Activity, Hours worked in the Holding and Operator Status for persons 10 years and over (iv) Level of Agricultural Activity (v) Livestock, Poultry and Domestic Animals (vi) Household Fishing Activities ( fishing methods, Number of fishing trips, persons involved in fishing, proportion of catch sold, number of canoes ,dinghies and outboard motors owned or hired. (vii)Number of Uga caught and method of Catching (viii) Consumption of Major crops( drinking Nuts, Matured Coconuts, Green and Ripe Bananas, Taro, Cassava and Papaya (ix) Number of Coconuts for Feeding Animals.

Cleaning operations

a. Checking, Editing and Coding It is standard practice that as each enumeration area was completed the forms were first checked by the field supervisors for missing information and obvious inconsistencies. Omissions and errors identified at this stage were corrected by the enumerators. The next stage was for the field supervisors to go through the completed forms again in the office to check in more detail for omissions and logical inconsistencies. Where they were found, the supervisors were responsible to take the necessary action. Once the questionnaires had been thoroughly checked and edited, they were then coded in preparation for data processing. Checking, editing and coding of the questionnaires in office were done after normal working hours as to ensure that the confidentiality of the survey is well observed.

b. Data Processing The data was entered using two office computers of Statistics Niue with a custom designed CSPro database software by a computer programmer from The National Statistics office of the Philippines. Data entry was successfully done in a week. The next stage of processing, on line editing and cleaning in preparation for tabulation was not straight forward as expected because of these issues: the programmer assigned by FAO for the census was based in the Philippines and was only available on part time basis, the census expert (consultant) was based in Samoa and was also available on part time basis while the rest of the team was in the Niue office. The ‘distance’ between the parties, the day and time differences had became a hurdle to the smooth running of the final stages of data processing, cleaning and tabulation of the data and not to mention the difficulties in the communication systems. The progress was very much depended on the availability of internet communications and they were times it has broken down. These composite issues have delayed the final stages of data processing dramatically.

Data appraisal

Overall, the standard of enumeration was high. A PES was conducted to evaluate the accuracy of the data. The PES used objective measurement techniques (compass and tape measure) to measure the physical area of the selected parcels of land. The results of the survey revealed differences between the areas recorded in the census interview and the physical area as measured.

Abstract

The census carried out in 1991 represents a primary source of data, which makes it possible to characterize the structure and operation of the agricultural and forestry sectors in the country. This is made possible through the collection of statistical data that support the decision making process which aims to increase production and productivity and raise the standard of living of rural families.

This census had the following phases: planning, experimentation, user consultation and decentralization. This was also coupled with the achievement of the following inputs: the implementation of four census events (2 trials, a survey, and a pilot census), various field tests, contributions from the advisory council, user workshops and planning committee, complemented by the exchange of experiences with international organizations. The operation of the ten regional directorates and the 32 state census coordinators allowed for the definition of objectives, structure, strategies, instruments and procedures to carry out the collection of information for the census.

The census had the following objectives: 1. Obtain, process and disseminate basic information on the productive structure of the agricultural and forestry sector. 2. Create sampling frames that serve as a basis for the development and integration of a system of continuous surveys of the agricultural and forestry sectors.

Geographic coverage

National Coverage

Analysis unit

Agricultural holdings

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face paper [f2f]

Cleaning operations

Data processing was carried out through the following stages:

1. Capture
2. Coverage verification
3. Electronic Clavification
4. Pre-Processing: (a) Purification and Filter, (b) Electronic Crop Relocation, and (c) Reformatting.
5. Normalization.
6. Electronic validation
7. Logical relations.
8. Preliminary Results
9. Final Results

Data appraisal

The activity of performing the census operation consisted of 2 stages: 1. Cartography and directories update: In this stage, due to the dynamism in the agricultural sector as a result of migration, land renting or abandonment, it was necessary to update the cartographic material and the register. This was done to update names of producers and identify the land that form the production units. The cartography and register were updated from July 29 to August 31, 1991, with the supervisors being responsible for this activity.

Cartography and registers are basic tools in census works, as they help identify producers and locate the land that makes up the production units. They also allow you to keep track of workloads and activities to be carried out, in order to achieve full coverage in the survey. Also, due to changes that occur in the rural area, the material that is available tends to be outdated. Thus, it is necessary to verify that the names of those responsible for the land at that time and those that were noted in the register were correct and that they correspond to the lands that appear in the cartography. To carry out this activity, the supervisors moved to the assigned localities (according to their work area), where they visit and collect information.

1. Census questionnaires: The questionnaires were administered in October, with the enumerators and their supervisors responsible for this activity. Enumerators were in charge of administering the questionnaires for rural and urban production units, in addition to the list of houses with agricultural activity. While the supervisors administered the questionnaires for agrarian communities and communal land.

The strategy implemented for this stage varied depending on the type of questionnaire and the number of inhabitants by location. They include:

A. Full coverage: The enumerators visited each and every dwelling in locations of less than 15,000 inhabitants in order to detect homes in which some agricultural activity was carried out.

B. Home visits: In localities over 15,000 inhabitants, the supervisor or enumerator went to specific homes that engaged in agricultural activities (pre-identified), or because they were some representative authority of the communal or agrarian community.

Abstract

In the past, the census of agriculture has aimed to provide data on the structure of agricultural holdings, with attention given to providing data for small administrative units and other detailed cross-tabulations of structural characteristics. Agricultural censuses have also been used to provide benchmarks to improve current crop and livestock statistics and to provide sampling frames for agricultural sample surveys. Previous agricultural censuses have focused on the activities of agricultural production units; that is, households or other units operating land or keeping livestock. They have not been seen as censuses of rural households.

This census is conducted to collect data needed by the government to make sound planning concerning the production of the agricultural produce.

Geographic coverage

Regional coverage

Analysis unit

Households

Universe

The agricultural holding is the enumeration unit, "comprising all land used and all livestock kept wholly or partly for agricultural production purposes. An individual or household may exercise management, jointly by two or more individuals or households, or by a juridical person such as a corporation, cooperative or government agency". The CA 2012/2013 covered the holdings in the household and the non-household sectors.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Enumeration area (EA): The 2012/13 Agricultural Census uses the maps of the previous population census enumeration areas (EAs). These maps divide the rural areas into E.A's. Identifying boundary features on land are roads, mountain ranges, and railway lines, etc. This was used to form EA boundaries. Each EA consists of a number of homesteads. For the purpose of agricultural census, these E.A's are verified. Normally in the agricultural census, an enumerator is assigned, at most, two E.A's or more. The EA is used as Primary Sampling Unit (PSU). The CA was a combination of: (i) a complete enumeration for certain items (in the first phase) and (ii) a sample enumeration of holdings for the items related to area and yield measurements and "general agricultural enquiries" (in the second phase). The census frame was built based on the EAs established for the Population and Housing Census (PHC) 2007.

Mode of data collection

Face-to-face [f2f]

Research instrument

One questionnaire with different modules was used for the holdings. Of the 16 core items required by the WCA 2010, the CA questionnaire covered 13 items.

(a) Holding location. (b) Legal status of holder. (c) Purpose of production. (d) Integration of holding with enterprises engaged in other economic activity (ies). (e) Basic demographic characteristics of holder and household. (f) Inventory of production factors: - Source of manpower used on the holding (family workers, hired agricultural workers); - Number and area of land parcels; - Area by land use; - Area harvested, by crop; - Number of cultivated trees by crop; - Number of livestock by type; - Type of machinery and equipment used; - Number of forest trees on the holding; - Agricultural buildings; (g) Tenure arrangements for production factors: - Land tenure; - Source of machinery and equipment used; (h) Other features: - Shifting cultivation; - Use of irrigation; - Drainage; - Fertilizers; - Pesticides; - High variety seeds; (i) Fishery or forestry activities if carried out on a holding; (j) Livestock system.

Cleaning operations

a. DATA PROCESSING AND ARCHIVING Manual data entry and editing (such as range and consistency edits, and imputations) were done using CSPro software. Tables were generated and edited using, respectively, CSPro and Microsoft Excel.

b. CENSUS DATA QUALITY The fieldwork was organized in several phases, to ensure the quality of the data collected. An enumerator was responsible for data collection in three EAs established for the PHC 2007, according to an adjusted workload. S/he was part of a team of ten enumerators, supervised by a field supervisor, who checked the coherence and quality of each filled questionnaire.

Data appraisal

Dissemination workshops were organized to release the census results. At the time of publication, the CA report with the final results had not yet been released.

Abstract

The 2001 Bulgaria Integrated Household Survey was conducted by BBSS Gallup International under the supervision of the World Bank. Because of the expected excessive level of attrition due to the large time lag from the last survey and the massive internal and external migration since 1997, for the purpose of this survey it was decided to draw a new cross-section of households. Using the same stratified two-stage cluster design adopted in 1995, a similar nationally-representative sample was drawn by the National Statistical Institute (NSI) from the pre-census listing of the 2001 Population Census.

The main objective of the survey was to provide comparable poverty figures with the previous studies, the questionnaire used is virtually identical to the one used in the previous surveys and when changes were introduced particular attention was paid to maintain consistency with the previous questionnaires.

Geographic coverage

National

Analysis unit

• Households
• Individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample size is 2,875 households

As in 1995, the original sampling plan called for the selection of five households in each of 500 randomly selected census clusters. In 2001, six households per cluster were provided by NSI to Gallup and the sixth household was used to replace households in the original sample in cases of refusal or absence. Each field substitution had to be verified by the team leader and approved by the field supervisor. A total of 2,500 households were finally interviewed. In addition, 133 Roma households were oversampled to allow more significant statistical comparisons of the group in some of the analyses. Detailed rules for the selection of the oversample were given to the enumerators and each selection was verified by the team leader.

Mode of data collection

Face-to-face [f2f]

Research instrument

Being a multi-purpose survey, the BIHS01 questionnaire follows the structure of a typical Living Standard Measurement Survey (LSMS). The survey collected exhaustive information for the estimation of a consumption aggregate. This includes food and non-food consumption expenditures as well as data for the imputation of housing rental value and the user value of durable goods. The questionnaire also contains comprehensive information for the estimation of income by source, as well as quite extensive information on health, education and the labor market.

The questionnaire has the following sections: Section 1: Household Roster Section 2: Migration Section 3: Education Section 4: Housing Section 5.1: Food Expenditure and Consumption Section 5.2: Purchase of Non-Food Commodities Section 6.1: Employment - status and history of employment Section 6.2: Main job - dependent activity (working for a salary or commission for somebody else) Section 6.3: Second - dependent activity (working for a salary or commission for somebody else) Section 6.4: Self employment - independent activity (working for yourself) Section 6.5: Agricultural land Section 6.6: Agriculture - crop production, yield Section 6.7: Agriculture assets Section 6.8: Agriculture - livestock: cattle, pigs, etc. Section 6.9: Other Farming Income and Costs Section 7.1: Remittances - Income Received from Absent Members of the Household or from Any Other Person. Section 7.2: Remittances - Absent Household Members and Other Persons Who Received Contributions from the Household Section 8.1: State old age pension Section 8.2: Private old age pension Section 8.3: Survivor's pension Section 8.4: Disability pension Section 8.5: Unemployment benefits - for all people above age 15 Section 8.6: Maternity and childcare benefits under the social assistance system
Section 8.7: In kind individual social benefits Section 8.8: Summary of child benefit allowance Section 8.9: Cash and in kind household social benefits Section 8.10: Other forms of revenue/debts Section 9.1: Household furniture and durable goods Section 9.2: Real estate assets Section 10: Health Status Section 11. Ethnicity of main respondent

Tabular data of population by age groups, race and gender, and the poverty by race is attached to the split tract geography to create this split tract with population and poverty data. Split tract data is the product of 2010 census tracts split by 2017 incorporated city boundaries and unincorporated community/countywide statistical areas (CSA) boundaries. The census tract boundaries have been altered and aligned where necessary with legal city boundaries and unincorporated areas, including shoreline/coastal areas. Census Tract:Every 10 years the Census Bureau counts the population of the United States as mandated by Constitution. The Census Bureau (https://www.census.gov/) released 2010 geographic boundaries data including census tracts for the analysis and mapping of demographic information across the United States. City Boundary:City Boundary data is the base map information for the County of Los Angeles. These City Boundaries are based on the Los Angeles County Seamless Cadastral Landbase. The Landbase is jointly maintained by the Los Angeles County Assessor and the Los Angeles County Department of Public Works (DPW). This layer represents current city boundaries within Los Angeles County. The DPW provides the most current shapefiles representing city boundaries and city annexations. True, legal boundaries are only determined on the ground by surveyors licensed in the State of California.Countywide Statistical Areas (CSA): The countywide Statistical Area (CSA) was defined to provide a common geographic boundary for reporting departmental statistics for unincorporated areas and incorporated Los Angeles city to the Board of Supervisors. The CSA boundary and CSA names are established by the CIO and the LA County Enterprise GIS group worked with the Los Angeles County Board of Supervisors Unincorporated Area and Field Deputies that reflect as best as possible the general name preferences of residents and historical names of areas. This data is primarily focused on broad statistics and reporting, not mapping of communities. This data is not designed to perfectly represent communities, nor jurisdictional boundaries such as Angeles National Forest. CSA represent board approved geographies comprised of Census block groups split by cities.Data Field:CT10: 2010 Census tractFIP17: 2017 City FIP CodeCITY: City name for incorporated cities and “Unincorporated” for unincorporated areas (as of July 1, 2017) CSA: Countywide Statistical Area (CSA) - Unincorporated area community names and LA City neighborhood names.CT10FIP17CSA: 2010 census tract with 2017 city FIPs for incorporated cities, unincorporated areas and LA neighborhoods. SPA12: 2012 Service Planning Area (SPA) number.SPA_NAME: Service Planning Area name.HD12: 2012 Health District (HD) number: HD_NAME: Health District name.POP17_AGE_0_4: 2017 population 0 to 4 years oldPOP17_AGE_5_9: 2017 population 5 to 9 years old POP17_AGE_10_14: 2017 population 10 to 14 years old POP17_AGE_15_17: 2017 population 15 to 17 years old POP17_AGE_18_19: 2017 population 18 to 19 years old POP17_AGE_20_44: 2017 population 20 to 24 years old POP17_AGE_25_29: 2017 population 25 to 29 years old POP17_AGE_30_34: 2017 population 30 to 34 years old POP17_AGE_35_44: 2017 population 35 to 44 years old POP17_AGE_45_54: 2017 population 45 to 54 years old POP17_AGE_55_64: 2017 population 55 to 64 years old POP17_AGE_65_74: 2017 population 65 to 74 years old POP17_AGE_75_84: 2017 population 75 to 84 years old POP17_AGE_85_100: 2017 population 85 years and older POP17_WHITE: 2017 Non-Hispanic White POP17_BLACK: 2017 Non-Hispanic African AmericanPOP17_AIAN: 2017 Non-Hispanic American Indian or Alaska NativePOP17_ASIAN: 2017 Non-Hispanic Asian POP17_HNPI: 2017 Non-Hispanic Hawaiian Native or Pacific IslanderPOP17_HISPANIC: 2017 HispanicPOP17_MALE: 2017 Male POP17_FEMALE: 2017 Female POV17_WHITE: 2017 Non-Hispanic White below 100% Federal Poverty Level POV17_BLACK: 2017 Non-Hispanic African American below 100% Federal Poverty Level POV17_AIAN: 2017 Non-Hispanic American Indian or Alaska Native below 100% Federal Poverty Level POV17_ASIAN: 2017 Non-Hispanic Asian below 100% Federal Poverty Level POV17_HNPI: 2017 Non-Hispanic Hawaiian Native or Pacific Islander below 100% Federal Poverty Level POV17_HISPANIC: 2017 Hispanic below 100% Federal Poverty Level POV17_TOTAL: 2017 Total population below 100% Federal Poverty Level POP17_TOTAL: 2017 Total PopulationAREA_SQMIL: Area in square milePOP17_DENSITY: Population per square mile.POV17_PERCENT: Poverty percentage.How this data created?The tabular data of population by age groups, by ethnic groups and by gender, and the poverty by ethnic groups is attributed to the split tract geography to create this data. Split tract polygon data is created by intersecting 2010 census tract polygons, LA Country City Boundary polygons and Countywide Statistical Areas (CSA) polygon data. The resulting polygon boundary aligned and matched with the legal city boundary whenever possible. Note:1. Population and poverty data estimated as of July 1, 2017. 2. 2010 Census tract and 2020 census tracts are not the same. Similarly, city and community boundary are not the same because boundary is reviewed and updated annually.

Abstract

The 2010 Census was undertaken to update current information on the size, sex, age, composition and other characteristics of Ghana's population and to ascertain the specific changes in these characteristics which had taken place since the last census was conducted in 2000. The Census was expected to ensure the continuation of a time series of demographic and socio-economic benchmark data at the national and sub-national levels and enhance the capability-building programme of the Statistical Service.

Geographic coverage

National coverage

Analysis unit

Household, individual

Universe

The 2010 census covered a de-facto population count of Ghana on Census Night (26th September 2010). These were all usual residents, infants sick as well as the mentally challenged, inmates of institutions. Out-door sleepers and all persons who spend census night within the boarders of Ghana, semi-stable floating population enumeration was done immediately after midnight of Census Night. Enumeration was done on Census Night of fishermen, other persons at sea, and other persons in Field Camps.

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

PHC-1A: Household questionnaire - admistered to household population. This questionnaire includes modules on Household roster, Usual household members absent, Emigration, Population, Mortality, ICT, Agriculture and Housing

PHC-1A: Usual Members Absent Continuation Sheet

PHC-1A: Emigration Continuation Sheet

PHC-1B: Group quarter questionnaire - administered to homeless households and group quarter population. This excludes usual members absent, emigration, mortality, ICT at household level, agricultural and housing modules.

PHC-1C: Group quarter questionnaire which was administered to individual members and later transferred to PHC-1B questionnaire

PHC-3: EA Result Sheet - Captured summary information on population by sex and the number of localities in each Enumeration Area (EA).

PHC-4: Final Summary Sheet - Captured summary information on the number of residential structures, number of households, population by sex and household and non-household population and the availability of telecommunication, education, health and toilet facilities in the locality.

Cleaning operations

The Census data editing was implemented at three levels:

1. Field editing by interviewers and supervisors
2. Office editing and coding of occupation and industry
3. Data cleaning and imputation

Data editing was partly manual and partly automatic. Occupation and Industry coding was done by the Field Supervisors but they were edited in the office after the field work. The questionnaire reference numbers were also reviewed as part of the preparatory activities before scanning.

Response rate

100 percent

Data appraisal

A post Enumeration Survey (PES) was conducted to assess the extent of coverage and content error. (See Adminstrative Report)

Split tract data is the intersection of 2020 census tracts by 2023 incorporated city boundaries and unincorporated countywide statistical areas (CSA) boundaries. The census tract boundaries have been altered and aligned where necessary with legal city boundaries and unincorporated areas, including along shoreline/coastal areas. This data is also known as the Split Tract data. This data can be used to estimate population changes over time. Census Tract:Every 10 years the Census Bureau counts the population of the United States as mandated by Constitution. The Census Bureau released 2020 geographic boundaries data including census tracts for the analysis and mapping of demographic information across the United States. City Boundary:City Boundary data is the base map information for the County of Los Angeles. These City Boundaries are based on the Los Angeles County Seamless Cadastral Landbase. The Landbase is jointly maintained by the Los Angeles County Assessor and the Los Angeles County Department of Public Works (DPW). This layer represents current city boundaries within Los Angeles County. The DPW provides the most current shapefiles representing city boundaries and city annexations. True, legal boundaries are only determined on the ground by surveyors licensed in the State of California.Countywide Statistical Areas (CSA):The countywide Statistical Area (CSA) was defined to provide a common geographic boundary for reporting departmental statistics for unincorporated areas and incorporated Los Angeles city to the Board of Supervisors. The CSA boundary and CSA names are established by the CIO and the LA County Enterprise GIS group worked with the Los Angeles County Board of Supervisors Unincorporated Area and Field Deputies that reflect as best as possible the general name preferences of residents and historical names of areas. This data is primarily focused on broad statistics and reporting, not mapping of communities. This data is not designed to perfectly represent communities, nor jurisdictional boundaries such as Angeles National Forest. CSA represent board approved geographies comprised of Census block groups split by cities.Data Field:CT20FIP23CSA: ID field (combination of 2020 census tract number, 2023 city FIP code and CSA name)CT20: 2020 Census TractFIP23: FIP code for legal cityCITY: Legal City Name (as of July 1, 2023)CSA: Countywide Statistical Area (CSA) and Los Angeles City neighborhood namesHow this data created?This polygon data is created by intersecting 2020 census tract polygons, LA Country City neighborhood polygons and Countywide Statistical Areas (CSA) data polygon. The resulting polygon boundary aligned and matched with the legal city boundary whenever possible. Updates:2023 July: The major updates include 2022 November Santa Clarita City annexation and Kinneloa Mesa community (previously it was a part of Unincorporated East Pasadena). This data also aligns with current city boundary along LA County shoreline areas.