Families of tax filers; Census families by age of older partner or parent and number of children (final T1 Family File; T1FF).

🔗 Check out my notebook here: Link

This dataset includes malnutrition indicators and some of the features that might impact malnutrition. The detailed description of the dataset is given below:

• Percentage-of-underweight-children-data: Percentage of children aged 5 years or below who are underweight by country.

• Prevalence of Underweight among Female Adults (Age Standardized Estimate): Percentage of female adults whos BMI is less than 18.

• GDP per capita (constant 2015 US$): GDP per capita is gross domestic product divided by midyear population. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in constant 2015 U.S. dollars.

• Domestic general government health expenditure (% of GDP): Public expenditure on health from domestic sources as a share of the economy as measured by GDP.

• Maternal mortality ratio (modeled estimate, per 100,000 live births): Maternal mortality ratio is the number of women who die from pregnancy-related causes while pregnant or within 42 days of pregnancy termination per 100,000 live births. The data are estimated with a regression model using information on the proportion of maternal deaths among non-AIDS deaths in women ages 15-49, fertility, birth attendants, and GDP measured using purchasing power parities (PPPs).

• Mean-age-at-first-birth-of-women-aged-20-50-data: Average age at which women of age 20-50 years have their first child.

• School enrollment, secondary, female (% gross): Gross enrollment ratio is the ratio of total enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown. Secondary education completes the provision of basic education that began at the primary level, and aims at laying the foundations for lifelong learning and human development, by offering more subject- or skill-oriented instruction using more specialized teachers.

Connecticut's Birth to Three System (B23) supports families with infants and toddlers that have developmental delays to learn new ways to make everyday activities enhance the child's development. Birth to Three is administered pursuant to Part C of the Individuals with Disabilities Education Act (IDEA). Once families with children below age 3 are referred, the child's development is evaluated for eligibility, and if eligible the family can receive supports until the child no longer has delays or until the child turns age 3. Because an infant can be referred within days of being born, a family may be enrolled for almost three full years. Connecticut's Birth to Three System publishes data annually by the fiscal and calendar year and longitudinally by birth cohort. CTData.org carries both sets of data, here and in 'Birth To Three Annual Data'. Birth cohort data looks at all children born in a particular year and tracks whether the family received B23 support. For example, the latest full year available in this dataset is for those children born in 2013 since they turned age 3 sometime in 2016. The 2013 data will tell you how many children there were whose families received support at some point during the first three years of the child's life. CTData calculates several indicators using total number of births in a town. This provides users with a general idea of the relative number of children in the community eligible for services. Using births is not perfect since families move in and out of town so it should not be used as an exact figure but as a general reference point. Below are how the indicators are calculated: % Referrals = Number referred divided by total number of births % Evaluations = Number evaluated divided by total number of births % Eligible = Number eligible divided by total number of births % Individual Family Service Plans (IFSP) = Number with IFSP divided by total number of births % Served = Number served divided by total number of births % Exited to Early Childhood Special Education = Number exited to early childhood special education divided by total number of births 'Referred that are Evaluated' represents the percent of children that were evaluated out of the total number of children referred to the Birth to Three System. 'Evaluated that are Eligible' represents the percent of children who were deemed eligible out of the total number of children that were evaluated. 'Eligible that Recieve IFSP' represents the percent of children whose family recieved an Individual Family Service Plan out of the total number of eligible children.

Introduction

Welcome to the Native American Child Faces Dataset, meticulously curated to enhance face recognition models and support the development of advanced biometric identification systems, child identification models, and other facial recognition technologies.

Facial Image Data

This dataset comprises over 3,000 child image sets, divided into participant-wise sets with each set including:

Diversity and Representation

The dataset includes contributions from a diverse network of children across Native American countries:

Quality and Conditions

To ensure high utility and robustness, all images are captured under varying conditions:

Metadata

Each facial image set is accompanied by detailed metadata for each participant, including:

This metadata is essential for training models that can accurately recognize and identify children's faces across different demographics and conditions.

Usage and Applications

This facial image dataset is ideal for various applications in the field of computer vision, including but not limited to:

Secure and Ethical Collection

Updates and

The following datasets are based on the children and youth (under age 21) beneficiary population and consist of aggregate Mental Health Service data derived from Medi-Cal claims, encounter, and eligibility systems. These datasets were developed in accordance with California Welfare and Institutions Code (WIC) § 14707.5 (added as part of Assembly Bill 470 on 10/7/17). Please contact BHData@dhcs.ca.gov for any questions or to request previous years’ versions of these datasets. Note: The Performance Dashboard AB 470 Report Application Excel tool development has been discontinued. Please see the Behavioral Health reporting data hub at https://behavioralhealth-data.dhcs.ca.gov/ for access to dashboards utilizing these datasets and other behavioral health data.

The Story of Our Children and Young People is a comprehensive overview of the wellbeing of our children and young people. The Story presents data across key indicators, mapped over six domains, measuring wellbeing from the antenatal period to young adulthood. The Story also highlights positive case studies and cultural stories of wellbeing which begin to tell the many stories presented across our community. Published biennially, data is presented for the Northern Territory and its six regions. In the 2021 Story, data is also presented by sub-region and/or Aboriginal status. For select measures, trend data is presented to facilitate a deeper understanding of changes over time. Together with the growing number of community stories, this provides an emerging network of information about children and young people to inform and guide policy, planning, decision-making and practice. An interactive data platform allows users to prepare and download data tables and graphs to meet individual needs.

The family is currently in a state of flux. The birthrate today is much lower than in past times. The number of new marriages is declining while the number of young people who stay single increases. Many people live in extramarital life partnerships. These new trends create problems, which politics, administration and various non-governmental organisations such as family relations have to overcome. To make this possible, it is necessary to have reliable information which has been non existent up to now. There has for instance been no statistical data on the number of stepchildren although more and more children affected by their parents divorce grow up with their parents’ new partners. Only with this survey, which asks questions on the existence of parents outside the household, the gap is closed. However, the older generation is also of interest. Little is known about their families. Normally only relatives living in the same household are recorded in the statistics. Therefore, many married couples are labelled childless although their children have only moved out. This makes the question on relatives outside the interviewees’ households necessary. Information on the existence of relatives and contacts with them are also necessary to appraise in how far relatives are or can be included in the care of the increasing number of elderly people. The special program consists of 4 parts: 1. questions on the existence of biological relatives (B 22 and B 23: to all persons) 2. questions on the birth of children (B 24 and B 25: to women over 15 B 26 to B 28: to women between 20 and 40) 3. questions on the moving out from the parents’ household (B 29 and B 30: to all persons between 15 and 60) 4. questions on marriage and divorce (B 31 to B 35: to all married, divorced and widowed persons between 15 and 60)

This dataset contains counts of live births for California counties based on information entered on birth certificates. Final counts are derived from static data and include out of state births to California residents, whereas provisional counts are derived from incomplete and dynamic data. Provisional counts are based on the records available when the data was retrieved and may not represent all births that occurred during the time period.

The final data tables include both births that occurred in California regardless of the place of residence (by occurrence) and births to California residents (by residence), whereas the provisional data table only includes births that occurred in California regardless of the place of residence (by occurrence). The data are reported as totals, as well as stratified by parent giving birth's age, parent giving birth's race-ethnicity, and birth place type. See temporal coverage for more information on which strata are available for which years.

This dataset contains Iowa households with and without children under 18 years old by household type for State of Iowa, individual Iowa counties, Iowa places and census tracts within Iowa. Data is from the American Community Survey, Five Year Estimates, Table B11005. Household type includes Total Households, Family - All Types, Family - Married Couple, Family - All Single Householders, Family - Male Householder - No Wife Present, Family - Female Householder - No Husband Present, Nonfamily - All Types, Nonfamily - Male Householder, Nonfamily - Female Householder, Total Households w/Minors, and Total Households w/o Minors. A family household is a household maintained by a householder who is in a family. A family group is defined as any two or more people residing together, and related by birth, marriage, or adoption. Householder refers to the person (or one of the people) in whose name the housing unit is owned or rented (maintained) or, if there is no such person, any adult member, excluding roomers, boarders, or paid employees. If the house is owned or rented jointly by a married couple, the householder may be either the husband or the wife.

Dataset population: Families in households/Dependent children in households

Dependent children in family

A dependent child is any person aged 0 to 15 in a household (whether or not in a family) or a person aged 16 to 18 who's in full-time education and living in a family with his or her parent(s) or grandparent(s). It does not include any people aged 16 to 18 who have a spouse, partner or child living in the household.

A family is defined as a group of people who are a:

• Married, same-sex civil partnership, or cohabiting couple, with or without child(ren)
• Lone parent with child(ren)
• Married, same-sex civil partnership, or cohabiting couple with grandchild(ren) but with no children present from the intervening generation
• Single grandparent with grandchild(ren) but no children present from the intervening generation.

Children in couple families need not belong to both members of the couple. For single or couple grandparents with grandchildren present, the children of the grandparent(s) may also be present if they are not the parents or grandparents of the youngest generation present.

Dataset population: Dependent children in families

Dependent children in family

A dependent child is any person aged 0 to 15 in a household (whether or not in a family) or a person aged 16 to 18 who's in full-time education and living in a family with his or her parent(s) or grandparent(s). It does not include any people aged 16 to 18 who have a spouse, partner or child living in the household.

A family is defined as a group of people who are a:

• Married, same-sex civil partnership, or cohabiting couple, with or without child(ren)
• Lone parent with child(ren)
• Married, same-sex civil partnership, or cohabiting couple with grandchild(ren) but with no children present from the intervening generation
• Single grandparent with grandchild(ren) but no children present from the intervening generation.

Children in couple families need not belong to both members of the couple. For single or couple grandparents with grandchildren present, the children of the grandparent(s) may also be present if they are not the parents or grandparents of the youngest generation present.

This dataset contains counts of live births for California as a whole based on information entered on birth certificates. Final counts are derived from static data and include out of state births to California residents, whereas provisional counts are derived from incomplete and dynamic data. Provisional counts are based on the records available when the data was retrieved and may not represent all births that occurred during the time period.

The final data tables include both births that occurred in California regardless of the place of residence (by occurrence) and births to California residents (by residence), whereas the provisional data table only includes births that occurred in California regardless of the place of residence (by occurrence). The data are reported as totals, as well as stratified by parent giving birth's age, parent giving birth's race-ethnicity, and birth place type. See temporal coverage for more information on which strata are available for which years.

This table contains 30 series, with data for years 1961 - 1971 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Unit of measure (1 items: Persons ...) Geography (1 items: Canada ...) Children born to ever-married women (10 items: Number of children born to ever-married women 15 years of age and over; total; Number of children born to ever-married women aged 15-19 years; Number of children born to ever-married women aged 20-24 years; Number of children born to ever-married women aged 25-29 years ...) Type of area (3 items: Total urban and rural areas; Rural; Urban ...).

The Monthly Child Care Services Data Report - Families Served by ZIP Code data set includes demographic data of parents and families of children receiving Child Care and Development Fund (CCDF) assistance. The Administration for Children and Families (ACF) Office of Child Care (OCC) collects data regarding the children and families served through the Child Care and Development Fund (CCDF) as well as the types of child care settings and facilities providing services. Each quarterly data set contains data aggregated by ZIP code for each month of the quarter. Counts less than 5 are masked with an asterisk (*) to protect the confidentiality of individuals in this report.

NHS-funded Community Services for children and young people aged 18 years or under using data from the new Children and Young People's Health Services (CYPHS) data set reported in England. The CYPHS is a patient-level dataset providing information relating to NHS-funded community services for children and young people aged 18 years or under. These services can include health centres, schools and mental health trusts. The data collected includes personal and demographic information, diagnoses including long-term conditions and childhood disabilities and care events plus screening activities.

It has been developed as part of the Maternity and Children's Data Set (MCDS) Project to achieve better outcomes of care for children and young people. It provides data that will be used to improve clinical quality and service efficiency, in a way that improves health and reduces inequalities.

These statistics are classified as experimental and should be used with caution. Experimental statistics are new official statistics undergoing evaluation. They are published in order to involve users and stakeholders in their development and as a means to build in quality at an early stage. More information about experimental statistics can be found on the UK Statistics Authority website.

This datas real-world trends in children's screen time usage. It includes data on educational, recreational, and total screen time for children aged 5 to 15 years, with breakdowns by gender (Male, Female, Other/Prefer not to say) and day type (Weekday, Weekend). The dataset follows expected behavioral patterns:

Screen time increases with age (~1.5 hours/day at age 5 to 6+ hours/day at age 15).

Recreational screen time dominates, making up 65–80% of total screen time.

Weekend screen time is 20–30% higher than weekdays, with a larger increase for teenagers.

Slight gender-based variations in recreational screen time.

The dataset contains natural variability, ensuring realism, and the sample size decreases slightly with age (e.g., 500 respondents at age 5, 300 at age 15).

This dataset is ideal for data analysis, visualization, and machine learning experiments related to children's digital habits. 🚀

Families and children in the UK by family type including married couples, cohabiting couples and lone parents. Also shows household size and people living alone.

The Maternity Indicators Data Set captures data relating to the woman at initial assessment and to mother and baby (or babies) for all births. This relates to initial assessment and birth activity undertaken in Wales only. Each Health Board must make available data in relation to the initial assessments and/or birth events which they managed.

For example, if they only carried out the initial assessment the Health Board would only be required to provide the initial assessment data. This is further detailed in the technical specification (see ‘return submission details’).

Where the initial assessment and birth events take place in different Health Boards, data will be linked nationally by the NHS Wales Informatics Service.

Velindre NHS Trust are excluded from this requirement, as they do not provide any maternity services.

Monthly activity data must include only initial assessment and birth activity that took place in the previous month.

This dataset requires additional governance approvals from the data provider before data can be provisioned to a SAIL project.

Introduction

Welcome to the South Asian Child Faces Dataset, meticulously curated to enhance face recognition models and support the development of advanced biometric identification systems, child identification models, and other facial recognition technologies.

Facial Image Data

This dataset comprises over 5,000 child image sets, divided into participant-wise sets with each set including:

Diversity and Representation

The dataset includes contributions from a diverse network of children across South Asian countries:

Quality and Conditions

To ensure high utility and robustness, all images are captured under varying conditions:

Metadata

Each facial image set is accompanied by detailed metadata for each participant, including:

This metadata is essential for training models that can accurately recognize and identify children's faces across different demographics and conditions.

Usage and Applications

This facial image dataset is ideal for various applications in the field of computer vision, including but not limited to:

Secure and Ethical Collection