This comprehensive report chronicles the history of women in the military and as Veterans, profiles the characteristics of women Veterans in 2009, illustrates how women Veterans in 2009 utilized some of the major benefits and services offered by the Department of Veterans Affairs (VA), and discusses the future of women Veterans in relation to VA. The goal of this report is to gain an understanding of who our women Veterans are, how their military service affects their post-military lives, and how they can be better served based on these insights.

NOTE: 2001-2013 enlisted totals include "cadets-midshipmen" so officer+enlisted=total. This may not be the correct assumption, but the historical tables only have "officer" and "enlisted" totals.

This dataset represents the total number of Female Officers and Non-Commissioned Members (NCMs) in the Canadian Armed Forces (CAF) from 1997 to 2022. Military Personnel Command (MPC) supports the requirement to release accurate and timely information to Canadians, in line with the principles of Open Government. MPC has made every attempt to ensure the accuracy and reliability of the information provided. However, data contained within this report may also appear in historic, current and future reports of a similar nature where it may be represented differently, and in some cases appear to be in conflict with the current report. MPC assumes no responsibility, or liability, for any errors or omissions in the content of this publication.

This dataset contains the tweet ids of 407,911 tweets, including tweets between October 1, 2021 and December 31, 2021. This collection is a subset of the Schlesinger Library #metoo Digital Media Collection.These tweets were collected weekly from the Twitter API through Social Feed Manager using the POST statuses/filter method of the Twitter Stream API.Please note that there will be no updates to this dataset.The following list of terms includes the hashtags used to collect data for this dataset: #metoo, #timesup, #metoostem, #sciencetoo, #metoophd, #shittymediamen, #churchtoo, #ustoo, #metooMVMT, #ARmetoo, #TimesUpAR, #metooSociology, #metooSexScience, #timesupAcademia, and #metooMedicine.Be aware that previous quarters (up to the first quarter of 2020) only include one hashtag: #metoo.Per Twitter's Developer Policy, tweet ids may be publicly shared for academic purposes; tweets may not. Therefore, this dataset only contains tweet ids. In order to retrieve tweets that are still available (not deleted by users) tools like Hydrator are available.There are similar subsets related to the Schlesinger Library #metoo Digital Media Collection available by quarter, as well as a full dataset with a larger corpus of hashtags.

SELECTED SOCIAL CHARACTERISTICS IN THE UNITED STATES VETERAN STATUS - DP02 Universe - Civilian population 18 Year and over Survey-Program - American Community Survey 5-year estimates Years - 2020, 2021, 2022 Veteran status is used to identify people with active duty military service and service in the military Reserves and the National Guard. Veterans are men and women who have served (even for a short time), but are not currently serving, on active duty in the U.S. Army, Navy, Air Force, Marine Corps, or the Coast Guard, or who served in the U.S. Merchant Marine during World War II. People who served in the National Guard or Reserves are classified as veterans only if they were ever called or ordered to active duty, not counting the 4-6 months for initial training or yearly summer camps.

The 2012 US Army Anthropometric Survey (ANSUR II) was executed by the Natick Soldier Research, Development and Engineering Center (NSRDEC) from October 2010 to April 2012 and is comprised of personnel representing the total US Army force to include the US Army Active Duty, Reserves, and National Guard. The data was made publicly available in 2017. In addition to the anthropometric and demographic data described below, the ANSUR II database also consists of 3D whole body, foot, and head scans of Soldier participants. These 3D data are not publicly available out of respect for the privacy of ANSUR II participants. The data from this survey are used for a wide range of equipment design, sizing, and tariffing applications within the military and has many potential commercial, industrial, and academic applications.These data have replaced ANSUR I as the most comprehensive publicly accessible dataset on body size and shape. The ANSUR II dataset includes 93 measurements from over 6,000 adult US military personnel, comprising 4,082 men (ANSUR_II_MALE_Public.csv) and 1,986 women (ANSUR_II_FEMALE_Public.csv).

The ANSUR II working databases contain 93 anthropometric measurements which were directly measured, and 15 demographic/administrative variables.

Much more information about the data collection methodology and content of the ANSUR II Working Databases may be found in the following Technical Reports, available from theDefense Technical Information Center (www.dtic.mil) through:

a. 2010-2012 Anthropometric Survey of U.S. Army Personnel: Methods and Summary
Statistics. (NATICK/TR-15/007)
b. Measurer’s Handbook: US Army and Marine Corps Anthropometric Surveys,
2010-2011 (NATICK/TR-11/017)

Military Personnel Command (MPC) supports the requirement to release accurate and timely information to Canadians, in line with the principles of Open Government. This dataset represents the intake of women into the Canadian Armed Forces (CAF) Regular Force from 1997 to 2022. MPC has made every attempt to ensure the accuracy and reliability of the information provided. However, data contained within this report may also appear in historic, current and future reports of a similar nature where it may be represented differently, and in some cases appear to be in conflict with the current report. MPC assumes no responsibility, or liability, for any errors or omissions in the content of this publication. The Commander of Military Personnel Command (MILPERSCOM) is also appointed as the Chief of Military Personnel (CMP).

Military Personnel Command (MPC) supports the requirement to release accurate and timely information to Canadians, in line with the principles of Open Government. This dataset represents the outflow of Female Officers and Non-Commissioned Members (NCMs) leaving the Canadian Armed Forces (CAF) Regular Force from 1997 to 2022. MPC has made every attempt to ensure the accuracy and reliability of the information provided. However, data contained within this report may also appear in historic, current and future reports of a similar nature where it may be represented differently, and in some cases appear to be in conflict with the current report. MPC assumes no responsibility, or liability, for any errors or omissions in the content of this publication. The Commander of Military Personnel Command (MILPERSCOM) is also appointed as the Chief of Military Personnel (CMP).

Women Veterans who receive maternity care through VA often have multiple medical conditions that can increase their risk of pregnancy complications. Unique to Veterans, experiencing a military deployment may increase the risk of pre-term birth. It is suggested that one of the reasons for this increased risk of pre-term birth may be that being deployed also increases the risk of developing post traumatic stress disorder (PTSD). Having PTSD can increase the risk of a spontaneous pre-term birth as well as preeclampsia and gestational diabetes.

The goal of this study was to compile and analyze data about incidents of domestic violence in San Diego County, California, in order to enhance understanding of the nature and scope of violence against women. The following objectives were set to achieve this goal: (1) to develop a standardized interview instrument to be used by all emergency shelters for battered women in the region, and (2) to conduct interviews with shelter staff. For this study, the San Diego Association of Governments (SANDAG) collected information about domestic violence in San Diego County from clients admitted to battered women's shelters. The Compilation of Research and Evaluation (CORE) intake interview (Part 1) was initiated in March of 1997. Through this interview, researchers gathered data over a 22-month period, through December 1998, for 599 clients. The CORE discharge interview (Part 2) was theoretically completed at the time of exit with each client who completed the CORE intake interview in order to document the services received. However, data collection at exit was not reliable, due to factors beyond the researchers' control, and thus researchers did not receive a discharge form for each individual who had an intake form. For Part 1 (Intake Data), demographic variables include the client's primary language, and the client and batterer's age, education, race, how they supported themselves, their annual incomes, and their children's sex, age, and ethnicity. Other variables cover whether the client had been to this shelter within the last 12 months, the kind of housing the client had before she came to the shelter, person's admitted along with the client, drug and alcohol use by the client, the batterer, and the children, relationship between the client and the batterer (e.g., spouse, former spouse), if the client and batterer had been in the military, if the client or children were military dependents, the client's citizenship, if the client and batterer had any physical/mental limitations, abuse characteristics (e.g., physical, verbal, sexual, weapon involved), and the client's medical treatment history (e.g., went to hospital, had been abused while pregnant, witnessed abuse while growing up, had been involved in other abusive relationships, had attempted suicide). Additional variables provide legal information (number of times police had been called to the client's household as a result of domestic violence, if anyone in the household had been arrested as a result of those calls, if any charges were filed, if the client or batterer had been convicted of abuse), if the client had a restraining order against the batterer, how the client found out about the shelter, the number of times the client had been admitted to a domestic violence shelter, the client's assessment of her needs at the time of admittance, and the interviewer/counselor's assessment of the client's needs at the time of admittance. Part 2 (Discharge Data) provides information on services the client received from the shelter during her stay (food, clothing, permanent housing, transitional housing, financial assistance, employment, education, medical help, assistance with retrieving belongings, assistance with retrieving/replacing legal documents, law enforcement, temporary restraining order), and services this client received as a referral to another agency (attorney, divorce, child care, counseling, transportation, safety plan, victim/witness funds, mental health services, department of social services, Children's Services Bureau, help with immigration, drug treatment).

This dataset contains the tweet ids of 464,168 tweets, including tweets between April 1, 2021 and June 30, 2021. This collection is a subset of the Schlesinger Library #metoo Digital Media Collection.These tweets were collected weekly from the Twitter API through Social Feed Manager using the POST statuses/filter method of the Twitter Stream API.Please note that there will be no updates to this dataset.The following list of terms includes the hashtags used to collect data for this dataset: #metoo, #timesup, #metoostem, #sciencetoo, #metoophd, #shittymediamen, #churchtoo, #ustoo, #metooMVMT, #ARmetoo, #TimesUpAR, #metooSociology, #metooSexScience, #timesupAcademia, and #metooMedicine.Be aware that previous quarters (up to the first quarter of 2020) only include one hashtag: #metoo.Per Twitter's Developer Policy, tweet ids may be publicly shared for academic purposes; tweets may not. Therefore, this dataset only contains tweet ids. In order to retrieve tweets that are still available (not deleted by users) tools like Hydrator are available.There are similar subsets related to the Schlesinger Library #metoo Digital Media Collection available by quarter, as well as a full dataset with a larger corpus of hashtags.

This feature class/shapefile contains locations of Hospitals for 50 US states, Washington D.C., US territories of Puerto Rico, Guam, American Samoa, Northern Mariana Islands, Palau, and Virgin Islands. The dataset only includes hospital facilities based on data acquired from various state departments or federal sources which has been referenced in the SOURCE field. Hospital facilities which do not occur in these sources will be not present in the database. The source data was available in a variety of formats (pdfs, tables, webpages, etc.) which was cleaned and geocoded and then converted into a spatial database. The database does not contain nursing homes or health centers. Hospitals have been categorized into children, chronic disease, critical access, general acute care, long term care, military, psychiatric, rehabilitation, special, and women based on the range of the available values from the various sources after removing similarities.

YouGov / Mayor of London Survey on women in the fire service and how this compares to the military, police and health service.

Today's Honour Roll recognizes the men and women of the military who fell on this day in history. This data is derived from the Canadian Virtual War Memorial (CVWM) – a registry of the more than 118,000 Canadians and Newfoundlanders who have given their lives serving Canada or the United Kingdom – established to allow all Canadians the opportunity to honour and remember their sacrifices.

Demographic, military service characteristics, and VHA healthcare (N = 40).

The US Department of Homeland Security, Homeland Infrastructure Foundations - Level Data (HIFLD) provided geographic shapefiles for United States hospitals. This feature class/shapefile contains locations of Hospitals for US territories of Puerto Rico. The dataset only includes hospital facilities based on data acquired from various state departments or federal sources which has been referenced in the SOURCE field. Hospital facilities which do not occur in these sources will be not present in the database. The source data was available in a variety of formats (pdfs, tables, webpages, etc.) which was cleaned and geocoded and then converted into a spatial database. The database does not contain nursing homes or health centers. Hospitals have been categorized into children, chronic disease, critical access, general acute care, long term care, military, psychiatric, rehabilitation, special, and women based on the range of the available values from the various sources after removing similarities. This feature class/shapefile contains Hospitals derived from various sources (refer SOURCE field) for the Homeland Infrastructure Foundation-Level Data (HIFLD) database. This feature class/shape file has a one-to-many relationship class (HospitalsToTrauma) relate with the “Trauma_Levels” table. This table captures the relationship between Hospitals and the state trauma level designations. “Hospitals” is the origin using STATE as the primary key. “Trauma_Levels” table is the destination using STATE as the foreign key. This dataset is based on information from the period 20120605-20170329.

The complete dataset for 50 States can be obtained from the HIFLD website: https://hifld-dhs-gii.opendata.arcgis.com/datasets/5eafb083e43a457b9810c36b2414d3d3_0 The shape file metadata can be obtained from: https://www.arcgis.com/sharing/rest/content/items/5eafb083e43a457b9810c36b2414d3d3/info/metadata/metadata.xml?format=default&output=html

Key points and clinical implications for firearm LMC with women veterans.