In 2023, there were 6,348 public social welfare specialists in Gyeonggi (Gyeonggi Province), South Korea. Seoul also had a high number of specialists, while other provinces had far less.

Number of employment insurance beneficiaries receiving regular income benefits by province and territory, declared earnings, sex, and age group, last 5 months.

As of 2023, approximately 40 percent of individuals, and 50 percent of households in South Africa benefited from social grants. Households that received at least one social grant were highest in the Eastern Cape province amounting to almost a 65 percent share. Additionally, individuals in the same province received the largest portion of grants in the country, at nearly 53 percent.

In 2022, 20.746 billion Canadian dollars were spent by the Quebec government on social assistance benefits. The largest expense for the provincial government was grants to general government units, totaling about 67.8 billion Canadian dollars in that year.

Poverty and low-income statistics by visible minority group, Indigenous group and immigration status, Canada and provinces.

Number of employment insurance beneficiaries by type of income benefits, age group and sex, last 5 months.

Data on visible minority by income, generation status, highest certificate, diploma or degree, age and gender for the population aged 15 years and over in private households in Canada, provinces and territories, census metropolitan areas, census agglomerations and parts.

If you’re a senior with low income, you may qualify for monthly Guaranteed Annual Income System payments.

Maximum payment and allowable private income amounts:

The guaranteed income levels for July 1, 2024 to June 30, 2025 are:

• $87 monthly for single seniors (maximum monthly payment amount), your annual private income must be less than $4,176
• $174 monthly for senior couples (maximum monthly payment amount), your annual private income must be less than $8,352

The data is organized by private income levels. GAINS payments are provided on top of the Old Age Security (OAS) pension and the Guaranteed Income Supplement (GIS) payments you may receive from the federal government.

Learn more about the Ontario Guaranteed Annual Income System

This data is related to The Retirement Income System in Canada

The Ministry reports the breakdown of the BC Employment and Assistance program each month by provincial electoral district. This data is from 1995 onwards and includes counts for cases, recipients and dependent children.

Abstract

Child labour is a critical issue in Rwanda. This issue is considered as a socialization factor and gives rise to the problem of children’s participation in improving socioeconomic life of their respective households, and even in improving that of the country. The purpose of the National Child Labour Survey is to generate data on child labour (including education, economic and non-economic activities) and embark on the process of creating a database containing both qualitative and quantitative data on the child labour phenomenon in Rwanda.

These objectives unfold as follows: -To collect information on characteristics, nature, extent and reasons influencing childlabour in Rwanda and assess working conditions and impact on children health, education and normal development of children; -To create a database (quantitative and qualitative) on child labour which can be regularly updated through additional surveys and other administrative documents; -To carry out a comprehensive analysis of the conditions of children in employment in Rwanda by presenting the structure of activities, working conditions and their effects on children.

The 2008 Rwanda National Child Labour Survey (2008-RNCLS) focused on children aged 5-17 years living in ordinary households countrywide. Street children and those living in institutions like prisons, hospitals, children living in orphanages and others not living in ordinary households were not focused on in the survey. Only households having children aged 5 -17 years were targeted by the 2008-RNCLS. In total, 5,510 households were selected to constitute the survey sample and among them 5,084 were successfully identified and interviewed during the field survey, which is a response rate of nearly 92%.

Geographic coverage

National coverage

Analysis unit

• Households
• Individuals

Universe

The National Child Labour Survey has covered children aged 5 to 17 years living in ordinary households countrywide.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample of the National Child Labour Survey is a stratified two-stage sampling. The primary sampling stage is a cluster which is constituted of one enumeration block (EB) as it was designed in 2002 Rwanda General Census of Population and Housing.

At first stage, enumeration areas constructed on the basis of the 2002 Rwanda General Census of Population and Housing served as sampling frame for the drawing of lots of a sample of 300 enumeration blocks or clusters with the distribution of 10 enumeration blocks per District. The drawing of lots has been carried out with a proportional probability to the size of each cluster. The size has been measured on the basis of the number of households having children aged 5 to 17 years that constitute each enumeration block, according to the 2002 Rwanda General Census of Population and Housing. To pick those households, one has considered the households which had children under 13 years old in 2002.

For the second stage where the sampling unit was a household, a household list was first updated in each EB selected at primary stage and then a constant number of households have been selected from the number of households that have children aged from 5 to 17 years, identified during households listing in each EB.

Sampling deviation

No deviation from the sapmling design.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire comprises of three main parts. The first part covers all household members and allows to collect general information on their socio-demographic characteristics, their economic activities and on perceptions of parents or guardians of children about child labour.

While the second part is about household characteristics and allow to collect information on housing and accommodation.

The third part focuses only on children and provides information on their education and their working status. It also provides information on the health and welfare of children in employment as well as their safety in the workplace. The questionnaire is appended to this report.

Cleaning operations

The coding of the 2008-RNCLS questionnaires was carried out from 23rd to 29th, July 2008. Previously, a cross checking of filled questionnaires was done from the first filled questionnaires received and was pursued during the coding.

Response rate

The sample of the 2008-RNCLS initially comprised of 5,510 households. Following some non response cases, the number of households which were interviewed was lower than had been anticipated in the sample. Non-response cases were due to many reasons including the lack of household location, the change of location of a household, the absence of household 13 members for interview, etc. In total 5,085 households were visited and interviewed during the 2008-RNCLS, representing a response rate of 92.3%.

Data appraisal

A series of data quality tables and graphs are available to review the quality of the data and include the following: - NUMBER OF ENUMERATION BLOCS AND HOUSEHOLDS SELECTED BY PROVINCE........................................................................................................................................................................11 - DISTRIBUTION OF SURVEYED POPULATION BY SEX AND AGE GROUP. ..................................................................................................................................................................................................14 - DISTRIBUTION OF SURVEYED POPULATION UNDER 18 YEARS OLD BY SEX AND AGE. ....................................................................................................................................................................16 - DISTRIBUTION OF HOUSEHOLDS (IN %) BY PROVINCE ACCORDING TO HOUSEHOLD SIZE ........ ...................................................................................................................................................17 - DISTRIBUTION OF HOUSEHOLDS BY ECONOMIC SECTORS OF HEADS OF HOUSEHOLD..................................................................................................................................................................18 - DISTRIBUTION OF HOUSEHOLDS BY PROVINCES ACCORDING TO WELFARE QUINTILE....................................................................................................................................................................19 - DISTRIBUTION OF CHILDREN AGED 5 - 17 YEARS BY STATUS OF ACTIVITY...........................................................................................................................................................................................22 - ACTIVITY STATUS OF CHILDREN AGED 5 - 17 YEARS BY SEX AND PROVINCE ...................................................................................................................................................................................23 - NUMBER AND PERCENTAGE OF CHILDREN AGED 7 - 17 YEARS ATTENDING SCHOOL ...................................................................................................................................................................25 - PERCENTAGE OF CHILDREN INVOLVED IN HOUSEHOLD CHORES BY AGE, SEX AND PROVINCE ................................................................................................................................................25 - AVERAGE NUMBER OF WORKING HOURS IN HOUSEHOLD CHORES FOR CHILDREN AGED 7-17 YEARS BY SEX, AGE GROUP AND SSHOOL ATTENDANCE...................................29 - NUMBER AND PERCENTAGE OF CHILDREN IN EMPLOYMENT AGED 5-17 YEARS BY SECTORS OF ECONOMIC ACTIVITIES AND PROVINCE ……...................................................... 30
- DISTRIBUTION (IN %) OF CHILDREN IN EMPLOYMENT BY SECTORS OF ACTIVITY AND SEX ............................................................................................................................................................30 - NUMBER AND PERCENTAGE OF CHILDREN IN EMPLOYMENT AGED 5-17 YEARS BY STATUS IN EMPLOYMENT....................................................................................................................31
- HOURS WORKED PER WEEK BY CHILDREN IN EMPLOYMENT BY STATUS OF ACTIVITY, SEX, AGE GROUP AND PROVINCE ...............................................................................................30 - NUMBER AND PERCENTAGE OF CHILD LABOURERS AGED 5-17 YEARS BY SEX, AGE GROUP AND PROVINCE .....................................................................................................................34 - NUMBER AND PERCENTAGE OF CHILDREN AGED 5-17 YEARS CARRYING OUT HAZARDOUS WORK BY SEX, AGE GROUP AND PROVINCE ................................................................36 - NUMBER AND PERCENTAGE OF CHILD LABOURERS AGED 5-17 YEARS BY BRANCHES OF ACTIVITIES, AGE GROUP, AND SEX......................................................................................38 - NUMBER AND PERCENTAGE OF CHILDREN AGED 5-17 YEARS INVOLVED IN HAZARDOUS WORK BY BRANCH OF ACTIVITIES, AGE GROUP, AND SEX..........................................40 - NUMBER AND PERCENTAGE OF CHILD LABOURERS BY STATUS IN EMPLOYMENT............................................................................................................................................................................42 - WORKPLACE OF CHILD LABOURERS BY SEX AND AGE GROUP

This table shows figures in the field of social affairs and employment per municipality (2015 breakdown), part of the country, province, COROP area and labor market region. They provide information about the implementation of the Participation Act in 2015. This concerns information about: - social assistance (social assistance density, inflow and outflow percentage of social assistance, outflow to work from social assistance), - reintegration (outflow to work after reintegration, persons with a social assistance benefit and also a reintegration provision, persons with a reintegration provision and also a social assistance benefit), - WSW employees. The figures on numbers of inhabitants per municipality, part of the country, province and COROP area may deviate slightly from figures published elsewhere on StatLine, as this table shows the number of inhabitants at year-end 2015, while elsewhere the number of inhabitants at the start of the reporting year is often shown. Furthermore, welfare-related figures may differ from other tables because only general assistance is shown here. Data available on: 2015 Status of the figures: the figures in this table are final. Changes as of September 20, 2021: None, this table has been discontinued. When will new numbers come out? Not applicable anymore.

This research freshly investigates the effect of business competition on national welfare in Indonesia. This research uses business competition index data obtained from the Indonesia Competition Commission (KPPU) and welfare indicators data collected from the Indonesian Bureau of Central Statistics (BPS) at the economic sectoral and provincial levels for the period 2018–2020. The relationship between business competition and welfare is estimated using pooled regression model combining year, economic sector, and province. This research also uses business competition index applying both same weights for all dimensions of competition and the weights derived from principal component analysis. This research finds that business competition has a positive effect on welfare as represented by gross regional domestic product, regional productivity, productivity growth, wages, and human development index. Furthermore, the regions with high scores on the competition index mostly come from Java Island. Therefore, Indonesian government must encourage the mainstreaming of business competition in all provinces in Indonesia.

In 2022, the number of workers at social welfare facilities in Seoul, South Korea, reached around 115.7 thousand. That year, the city of Sejong saw a huge increase in workers, while Gyeonggi (Gyeonggi Province) and Gyeongnam (South Gyeongsang Province) recorded a large decrease.

Low income cut-offs (LICOs) before and after tax by community size and family size, in current dollars, annual.

Abstract

Since its inception in the early 1990s, the Welfare Monitoring Survey has played a crucial role as a tool for guiding policy decisions, and particularly those that are aimed at welfare improvements. Previous welfare monitoring surveys, for example, have shown that nearly half of the Kenyan population is. living in Absolute Poverty, and that poverty in general is on the increase. This revelation has in the recent past led to a number of Government measures to curb the deterioration in welfare.

The latest poverty estimates date back to the second Welfare Monitoring Survey (WMSII) of 1994, in which rural poverty was estimated at 46% and urban poverty at 29%. Since current information on the nature of poverty is essential for designing more poverty-sensitive strategies, the purpose of this report is to update 1994 poverty levels through the findings of the third Welfare Monitoring Survey (WMSIII), carried out between March and May 1997.

Geographic coverage

National Coverage

Analysis unit

Household, Individual

Universe

The survey covered all de jure households and household members (usual residents) from the sampled areas.

Kind of data

Sample survey data [ssd]

Sampling procedure

WMS III had a sample size of 10,873 households drawn from 1,107 clusters of the National Sample Survey and Evaluation Programme (NASSEP III). A three-stage sampling scheme was used, First Stage (EA selection within the district), Second Stage (Cluster selection), and Third Stage (Household selection).

Sampling deviation

Efforts to cover the whole country were unsuccessful, primarily due to the lack of adequate resources and insecurity in some districts. It was only possible to capture urban clusters in Gahissa and Wajir districts of North Eastern province while nowhere in Mandera was captured. In Rift Valley province, Samburu, and Turkana districts were not covered and in Eastern province, rural clusters in Isiolo were not captured.

Mode of data collection

Face-to-face [f2f]

Research instrument

Two sets of questionnaires were administered during the survey at different intervals. Phase one covered the core module; phase two administered Agriculture and non-agricultural income modules. The first set of questionnaires, referred to as the Core Welfare Indicators Questionnaire (CWIQ), had two sections as indicated below: a) Core Welfare Indicators Section I Demographic and Social Amenities Part I - Household Roster, covering demographics of household members, Health and family insurance, covering employment of members aged 5 years and above. Part II - Child roster (anthropometry). Part III - Household amenities. Part IV - Household assets Section II Household Expenditure Module

(b) Agriculture Questionnaire and Non Agricultural Income The second set of questionnaires covered agriculture activities for rural households and non-agricultural income for both rural and urban households. The module consisted of six parts, as outlined below: - Farming and agricultural services - Holding characteristics, crops and livestock production Non-agricultural income from informal sector activities Farm labour - General farm productivity constraints - Changes in agricultural production and food consumption.

Apart from the questionnaires administered during the survey, an additional module on prevailing rurallurban retail prices of essential commodities was also implemented. Supervisory duties during data collection were carried out by a team of 40 professionals drawn from Ministry headquarters, with support from respective district statistical officers. As previously mentioned, only non-ASAL districts were covered during the survey.

Cleaning operations

Data editing for the survey took place at the following stages : - Office editing and coding before the scanning of the questions and Structure checking and completeness

In 2021, 400 million Canadian dollars was spent by the Newfoundland and Labrador government on social assistance benefits. The largest expense for the provincial government in that year were grants to general government units, totaling to about 4.23 billion Canadian dollars.

This dashboard illustrates aggregated statistics on the status, actions, outcomes, and prosecutions from inspections conducted by the Manitoba Animal Welfare Program’s Animal Protection Officers (APO). This dashboard illustrates aggregated statistics on the status, actions, outcomes, and prosecutions from inspections conducted by the Manitoba Animal Welfare Program’s Animal Protection Officers (APO). The data is summarized on a quarterly basis, from 2016 to present. This dashboard will be updated on a quarterly basis with data from the Provincial Animal Welfare Program. The data table used for this dashboard reflects Manitoba Animal Welfare (AW) Program – Case Outcomes. The data table used for this dashboard is Manitoba Animal Welfare Program – Case Outcomes. There are two charts for this dashboard: Inspection Outcomes: This is a bar chart that ranks case outcomes from inspections conducted for assigned cases, in ascending order, for the user-selected time period. Prosecutions: This is a bar chart that ranks prosecution types associated with each assigned cases, in ascending order, for the user-selected time period. There are five indicators for this dashboard: Concerns Reported: This indicator displays the number of concerns reported for assigned cases in the user-selected time period. Inspections Conducted: This indicator displays the number of inspections conducted for assigned cases in the user-selected time period. Tickets Issued: This indicator displays the number of tickets issued for all assigned cases in a user-selected time period. Court Prosecutions: This indicator displays the number of court prosecutions for all assigned cases in the user-selected time period. Appeals Made: This indicator displays the number of appeals made for assigned cases in the user-selected time period. For more information, please refer to the Animal Welfare Main Page.

This data set records the statistical data of the composition of retirement, retirement and retirement insurance benefits in Qinghai Province from 2001 to 2006, which is divided by industry, region, affiliation and registration type. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of six tables Composition of retirement, retirement and retirement insurance benefits in 2001.xls Composition of retirement, retirement and retirement insurance benefits in 2002.xls Composition of retirement, retirement and retirement insurance benefits in 2004.xls Composition of retirement, retirement and retirement insurance benefits 2006.xls Composition of retirement, retirement and retirement insurance benefits in 2003.xls Composition of employee insurance and welfare expenses 1998.xls The data table structure is the same. There are 7 fields in the data table of retirement benefits and retirement expenses in 2001, for example: Field 1: Department Field 2: Total Field 3: leave money Field 4: pension Field 5: retirement cost of living Field 6: medical and health expenses Field 7: other

Abstract

The PSLM Project is designed to provide Social & Economic indicators in the alternate years at provincial and district levels. The project was initiated in July 2004 and will continue up to June 2015. The data generated through surveys is used to assist the government In formulating the poverty reduction strategy as well as development plans at district level and for the rapid assessment of program in the overall context of MDGs. As such this survey is one of the main mechanisms for monitoring MDGs indicators. It provides a set of representative, population-based estimates of social indicators and their progress under the PRSP/MDGs. For Millennium Development Goals (MDGs), UN has set 18 targets for 48 indicators for its member countries to achieve by 2015. Pakistan has committed to implement 16 targets and 37 indicators out of which 6 targets and 13 indicators are monitored through PSLM Surveys. The PSLM surveys are conducted at district level and at Provincial level respectively at alternate years. PSLM District level survey collects information on key Social indicators whereas through provincial level surveys (Social & HIES) collects information on social indicators as well as on Income and Consumption while in specific sections also information is also collected about household size; the number of employed people and their employment status, main sources of income; consumption patterns; the level of savings; and the consumption of the major food items. However, Planning Commission also uses this data for Poverty analysis.

Another important objective of the PSLM Survey is to try to establish the distributional impact of development programs; whether the poor have benefited from the program or whether increased government expenditure on the social sectors has been captured by the better off. The sample size of PSLM surveys district level is approximately 80000 households and approximately 18000 at Provincial level.

Main Indicators: Indicators on Demographic characteristics, Education, Health, Employment, Household Assets, Household Amenities, Population Welfare and Water Supply & Sanitation are developed at National/Provincial /District levels.

Geographic coverage

National coverage

Analysis unit

Households and Individuals

Universe

The universe of this survey consists of all urban and rural areas of all four provinces, AJK and Gilgit Baltistan. FATA and Military restricted areas have been excluded from the scope of the survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame: Pakistan Bureau of statistics PBS has developed its own urban area frame. Each city/town is divided into enumeration blocks. Each enumeration block is comprised to 200-250 households on the average with well-defined boundaries and maps .The list of enumeration blocks as updated from field on the prescribed Performa by Quick Count Technique in 2013 for urban and the list of villages/mouzas/dehs or its part (block), updated during House listing in 2011 for conduct of Population Census, are taken as sampling frame. Enumeration blocks and villages are considered as Primary Sampling Units (PSUs) for urban and rural domains respectively. A project to update the rural blocks is currently in hand.

Stratification Plan

Urban Areas: Large sized cities having population five laces and above have been treated as independent stratum. Each of these cities has further been sub-stratified into low, middle and high income groups. The remaining cities/towns within each defunct administrative division have been grouped together to constitute an independent stratum.

Rural Areas: The entire rural domain of a district for Khyber Pakhtunkhwa, Punjab, and Sindh provinces has been considered as independent stratum, whereas in Balochistan province defunct administrative division has been treated as stratum.

Sample Size and its Allocation: To determine optimum sample size for this survey, 6 indicators namely Literacy rate, Net enrolment rate at primary level, Population 10+ that ever attended school, Contraceptive prevalence of women age 15-49 years, Children age 12-23 months who are fully immunized and post natal consultation for ever married women aged 15-49 years were taken into consideration. Keeping in view the prevalence of these indicators at different margin of errors, reliability of estimates and field resources available a sample of size 19620 households distributed over 1368 PSUs (567 urban and 801 rural) has been considered sufficient to produce reliable estimates in respect of all four provinces with urban rural breakdown, however data was collected from 1307 PSU’S by covering 17989 household.

Sample Design: A two-stage stratified sample design has been adopted for this survey.

Selection of primary sampling Units (PSUs): Enumeration blocks in urban and rural domains have been taken as PSUs. In urban and rural domains sample PSUs from each stratum have been selected by PPS method of sampling scheme; using households in each block as Measure of size (MOS).

Selection of Secondary Sampling Units (SSUs): Households within PSU have been considered as SSUs. 16 and 12 households have been selected from urban/rural domains respectively by systematic sampling scheme with a random start.

Sampling deviation

Out of 1368 PSUs, of all four provinces 61 PSUs (11 urban and 50 rural PSUs) of Balochistan were dropped due to bad law and order situation and the remaining 1307 PSUs (556 urban and 751 rural) comprising 17989 households were covered.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

At both individual and household level, the PSLM Survey collects information on a wide range of topics using an integrated questionnaire. The questionnaire comprises a number of different sections, each of which looks at a particular aspect of household behavior or welfare. Data collected under Round IX includes education, diarrhea, immunization, reproductive health, pregnancy history, maternity history, family planning, pre and post-natal care and access to basic services.

Cleaning operations

Data quality in PSLM Survey has been ensured through a built in system of checking of field work by the supervisors in the field and by the in charge of the concerned Regional/Field offices. Teams from the headquarters also pay surprise visits and randomly check the work done by the enumerators. Regional/ Field offices ensured the data quality through preliminary editing at their office level. The entire data entry was carried at the PBS headquarter Islamabad and specially designed data entry programme had a number of built in consistency checks.

Data appraisal

To determine the reliability of the estimates confidence interval and Standard error of important key indicators have been worked out and are attached at the end of each section of the survey report, provided under the 'Related Materials' tab

The data set records the situation of special care and social relief in Qinghai Province, and the data is divided according to the situation of special care and social relief in Qinghai Province. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of three data tables Special care and social relief in the whole province, 1998.xls, Special care and social relief in the whole province, 1999.xls, The situation of special care and social relief in the whole province was analyzed in 2000.xls. The data table structure is the same. For example, there are five fields in the data table of the province's preferential care and social relief in 1998 Field 1: preferential treatment object Field 2: Unit Field 3: Total Field 4: social relief target Field 5: Unit