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.

This infographic shows not only service members who died in battle, but all those who have served and died since their military service. It also highlights the memorial benefits VA provides to those who have served and died.

Information about the types of eating disorders, some reasons why the military community are at risk, warning signs and how to get help. The Missouri Eating Disorders Council (MOEDC) created this document so support service members, veterans and their families.

Historical chart and dataset showing Japan military size by year from 1985 to 2020.

Historical chart and dataset showing China military size by year from 1985 to 2020.

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Historical chart and dataset showing Indonesia military size by year from 1985 to 2020.

Historical chart and dataset showing San Marino military size by year from N/A to N/A.

With more than 1,500 individual entries, this is the inaugural instalment of my research database collated in the framework of the Project Forgotten Soldiers: Jewish Military Experience in the Habsburg Monarchy. This is an open access database, and everyone is welcome to use it according to their own scholarly and personal interests. In 1,189 cases we have official documented records confirming the soldiers were Jewish. In another 313 entries I was able to identify likely Jewish soldiers based on circumstantial evidence cross-referencing names and places of birth, with the presence of confirmed Jewish soldiers drafted into the same units as part of the same recruitment drive. This dataset further includes evidence for 156 spouses and 47 children. While military records do mentions these, their number suggests that the Habsburg army preferred to enlist unmarried men.

The database is structured in a similar way to an official individual entry in the Habsburg military records. These were arranged in tables, with soldiers listed by seniority. Name, place and land of birth are followed by age and religion. This latter rubric allows identifying the bulk of the Jewish soldiers. Also included in the record is marital status, profession (if any), number, names and ages of children (if any), followed by a short summary text of the soldier’s service itinerary. While not always consistent in detail, these texts mention enlistment dates, transfers between units, promotions, desertions, periods as prisoner of war and military awards (if any). I have taken the material from the personal records and added several additional parameters:

• The soldiers are entered into the database according to their date of enlistment. This is followed by a colour-coded table showing their years of service. To see the meaning of the different colours employed, scroll to the legend at the end of the dataset.
• Following the years of service, we see the date when the soldier left service (final year in service for incomplete service records). When known, the reason the soldier left the army is given (discharge/ death/ desertion etc).
• Then come the three most important columns within the table: service record, primary sources and units. At first glance, these columns have only a few letters and numbers, but bring your mouse courser onto the relevant field marked with red triangles. An additional window will then open:

a. Service Record: Shows the entire service record of the soldier arranged by date. I use original German as it appears in the archival records. If you see spelling differences with modern German – they are there for a reason.

b. Primary Sources: Provides the information on all the archival records consulted to reconstruct the service itinerary. The number in the field denotes the number of the archival cartons consulted.

c. Units: Number of units in which a soldier serves. Bringing the cursor on to the field will open their list. Most Jewish soldiers served in the line infantry (IR) and the Military Transport Corps (MFWK or MFK). However, there were also Jewish sharpshooters, cavalrymen, gunners and even a few members of the nascent Austrian Navy.

• The next two columns provide entries of the soldier’s conduct and medical condition, which in Habsburg military jargon was referred to rather callously as Defekten. I note the original medical diagnoses verbatim. When possible to identify, I note the modern medical term.
• General database-wide parameters are then noted in the next part of the table. Among others, it provides information on enlistment type (conscript/ volunteer?), main branches of service (such as Infantry/ Cavalry/ Artillery), and roles within the military (such as non-commissioned officers/ drummers/ medics).
• Concluding this part of the table are columns covering desertions, periods as prisoner of war and awards of the army cannon cross (for veterans of 1813-14) and other military awards.
• The last column provides the original German outtake rubric as to how the soldier left service. In special cases, additional service notes are provides on the right.

How to use this dataset

This depends on what you are looking for. Firstly, download the dataset on to your computer via the link provided below. It is a simple Excel file which is easy to work with. If you wish to find out whether one of your ancestors served in the Habsburg army, use a simple keyword search. Please note that in our period there was no single accepted orthography meaning that some letters were used interchangeably (for instance B/P; D/T). There were also various patronymic suffices used in different parts of the monarchy (-witz in German/ -wicz in Polish/ -vits in Hungarian). Habsburg military clerks were mostly German speakers who often recorded the name phonetically. For instance, Jankel/ Jankl/ Jacob/ Jacobus all denote the same name. A Jewish teenager who identified himself as Moische when first reporting to duty, may have stayed so in the military records for decades, even if he was already a non-commissioned officer whose subordinates referred to as Herr Corporal.

If you study the history of concrete Jewish communities, use the keyword search and the filter option to find entries in the database where this locality is mentioned. Some places like Prague and Lublin could be identified effortlessly. In other cases (and see the above point on German-speaking clerks), place names were recorded phonetically. The military authority usually stuck to official Polish names in Galicia, and Hungarian in the Lands of the Crown of St. Stephan. In reality, a Jewish recruit from Transcarpathian Ruthenia could have his place of birth recorded in Hungarian, Romanian or Rusin. When I could not identify the place in question, I marked it with italics. Do you think you identified something I could not? Excellent! Then please write me, and I will correct the entry in the next instalment of this database.

I should stress that, currently, the database is not statistically representative. I have worked chronologically, meaning that there are disproportionally more entries for Jewish soldiers from the Turkish War, the first two Coalition Wars, and the Wars of 1805 and 1809. If you look at some of my other databases (for instance, that of the 1st Line Infantry Regiment 'Kaiser'), you will find least as many Jews who served in the wars of 1813-15. I will cover these in due course. This said, using the filter option of the Excel sheet, you can already make some individual queries. For instance, did Jewish grenadiers meet the minimal height requirement to be eligible for transfer into the elite infantry? (Hint: they did not!) If you are interested in the historical study of nutritional standards, compare the height of the soldiers with their year and place of birth. In my other project, I made calculations of the average height of Habsburg soldiers and I can already reveal that Jewish conscripts were, on average, several centimetres smaller than their non-Jewish comrades drafted in the same annual intake. Whatever stereotypes said, most Jews in the Habsburg Monarchy around 1800 were very poor and the sad fact of malnutrition as a child is reflected in their height as adults.

I should stress that this is a cumulative database. ZENODO has an excellent feature allowing updated versions to supersede earlier files while retaining the same DOI (Digital Object Identifier) and metadata. As my research progresses, I plan to upload new versions of this database bi-annually. This includes not only adding new entries, but also expanding and correcting existing ones. It might well be that the service record of a soldier covered up to 1806 will be brought to a later date, possibly even to his discharge from the army. If you have not found whom you are looking for, or if you want to work with larger samples for your research, visit this page again in a few months’ time. And if you do use this database for scholarly research (by all means, please do), do not forget to cite it as you would cite any other item in your bibliography! If you are a museum professional and you want to employ material from your database to illustrate your exhibitions, you are welcome, but please cite this resource for others to learn. Links to this database will also be appreciated.

Historical chart and dataset showing Egypt military size by year from 1985 to 2020.

Historical chart and dataset showing Guatemala military size by year from 1985 to 2020.

Historical chart and dataset showing Nepal military size by year from 1985 to 2020.

Content

Lists the military spending, GDP, and population estimate for the US each year from 1960 to 2020.

Acknowledgements

Banner image source: https://unsplash.com/photos/BQgAYwERXhs

Historical chart and dataset showing U.K. military size by year from 1985 to 2020.

Analysis of ‘Doctoral Boards in Military Academies in Romania’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/gpreda/doctoral-boards-in-military-academies-in-romania on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

Doctoral Studies in domains like Military, Intelligence or Police are not something we expect to be very frequent. Quite amazingly, it appears to be a significant number of Doctoral studies conducted over a short period in Romania in the Doctoral Schools associated with these Military Academies.

The data was initially in Romanian. We translated the column titles and the board members roles. We didn't translated the board members military grades and academic titles. Also, we didn't translated the titles of the Doctoral Thesis.

We show here a collection of

Content

This dataset contains Doctoral Boards from Defense (Military), Intelligence and Police Academy in Romania, as following: * National Defense Academy - data from 2007 to 2017; * National Intelligence Academy - data from 2010 to 2017; * Police Academy - data from 2004 to 2009.

Acknowledgements

We would like to thank to the respective Military, Intelligence and Police Academies for offering, as the Romanian Law is requiring, access to their data.

Inspiration

Use this data to understand who is coordinating the doctoral boards, who are most frequent doctoral advisors, who is repeatedly present in boards in one or multiple academies.

Could you see patterns, frequent apparitions? How many doctoral thesis can one single adviser have per year? And in how many doctoral boards is someone chairman or reviewer (simple member)?

--- Original source retains full ownership of the source dataset ---

Military Expenditure in Russia increased to 148967.30 USD Million in 2024 from 109203.60 USD Million in 2023. Russia Military Expenditure - values, historical data, forecasts and news - updated on July of 2025.

The Freikorps Grün Loudon started as a German mercenary formation raised in spring 1790 to provide the Habsburg army with a light infantry force against the short-lived Brabant Republic. The Freikorps continued to serve during the First Coalition War against Revolutionary France (1792-97). As the conflict dragged on, the Rhineland, which served as its primary recruitment area was occupied by the enemy. As a result, the Freikorps shifted its main recruitment efforts to the Habsburg province of Galicia where a large Jewish population lived. The first Jews volunteers were enlisted in spring 1796. Within a year, Jewish soldiers comprised more than one per cent of the unit's strength. This proportion was kept until the Freikorps was disbanded in summer 1798.

With a total number of 27 individual entries, this dataset covers every single Jewish soldier who served in the unit. In addition to basic bibliographical information, the dataset includes reconstructions of complete service itineraries. Some of these are so detailed that the whereabouts and doings of individual soldiers could be traced month after months. After Freikorps Grün Loudon was disbanded, 22 surviving Jewish veterans were transferred to the 3rd and 4th Light Infantry Battalions. Their subsequent service and eventual fates are covered as well. In the dataset includes partial information about three spouses and two children, whose their existence can be discerned from soldiers' personal records.

In terms of their service experiences, the Jewish members of the Freikorps Grün Loudon did not differ much from other mercenary soldiers of that period. As implied by their name, Freikorps units did not form part of the standing army. Manned by foreign renegades and local volunteers, their soldiers were considered more expandable, and Freikorps used to suffer high combat losses. Tactically, Freikorps were often divided into small raiding detachments, which meant their soldiers often remained outside of the direct supervision of their officers. This resulted in high desertion rates. At the same time, the Freikorps also had a committed core of highly-dedicated professional soldiers. Among the veterans of the Freikorps Grün Loudon was Samuel Prager – one of the first documented Jewish soldiers in modern history to rise to the rank of Company Sergeant Major.

For more information on the Freikorps Grün Loudon, see:

Alfons von Wrede, Geschichte der k. und k. Wehrmacht, 5 Vols., (Vienna: Seidel, 1898–1905), Vol. 2, pp. 445-6.

For more information how to identify Jewish soldiers in Habsburg military records, see:

Ilya Berkovich, 'Nachweis von Konfession und Religion in habsburgischen Militärmatriken', Die Habsburgermonarchie: Fragen, Quellen und Ergebnisee zur Geschichte der Neuzeit (Blog), (10 January 2020).

Historical chart and dataset showing Pakistan military size by year from 1985 to 2020.

The Battle of Nashville was the pivotal conflict of the Civil War. The Union troops required an extraordinary amount of labor to build a system of fortifications, trenches, redoubts and other wartime infrastructure to successfully capture and defend the city. With a mix of enslaved and free laborers, some of whom were impressed and others who volunteered their time and expertise, Nashville became the most fortified city in the war. Previously, the number of laborers necessary to complete such a monumental task was estimated at just under 3,000. The team used two different types of documents to add to this number: One, we extracted information about additional unlisted laborers from military correspondence regarding their claims and the claims of their widows, wives, and descendants. Two, we merged multiple lists created by various Federal officers that kept track of the Black laborers with whom they worked at various sites in and around the city in the Spatial Historian program. Through comparing these lists with the original labor rolls generated by General Morton, the team was able add an additional ~2,000 people to the toll, for a total of ~5,000 laborers who worked on Nashville’s defenses during the Civil War. This article expands on the process of extracting community-sourced data and linking it to previous datasets in order to create the most complete and recent count of enslaved and free Black laborers whose labor and craftsmanship in Nashville’s defenses helped bring the Civil War to its end.

analyze the current population survey (cps) annual social and economic supplement (asec) with r the annual march cps-asec has been supplying the statistics for the census bureau's report on income, poverty, and health insurance coverage since 1948. wow. the us census bureau and the bureau of labor statistics ( bls) tag-team on this one. until the american community survey (acs) hit the scene in the early aughts (2000s), the current population survey had the largest sample size of all the annual general demographic data sets outside of the decennial census - about two hundred thousand respondents. this provides enough sample to conduct state- and a few large metro area-level analyses. your sample size will vanish if you start investigating subgroups b y state - consider pooling multiple years. county-level is a no-no. despite the american community survey's larger size, the cps-asec contains many more variables related to employment, sources of income, and insurance - and can be trended back to harry truman's presidency. aside from questions specifically asked about an annual experience (like income), many of the questions in this march data set should be t reated as point-in-time statistics. cps-asec generalizes to the united states non-institutional, non-active duty military population. the national bureau of economic research (nber) provides sas, spss, and stata importation scripts to create a rectangular file (rectangular data means only person-level records; household- and family-level information gets attached to each person). to import these files into r, the parse.SAScii function uses nber's sas code to determine how to import the fixed-width file, then RSQLite to put everything into a schnazzy database. you can try reading through the nber march 2012 sas importation code yourself, but it's a bit of a proc freak show. this new github repository contains three scripts: 2005-2012 asec - download all microdata.R down load the fixed-width file containing household, family, and person records import by separating this file into three tables, then merge 'em together at the person-level download the fixed-width file containing the person-level replicate weights merge the rectangular person-level file with the replicate weights, then store it in a sql database create a new variable - one - in the data table 2012 asec - analysis examples.R connect to the sql database created by the 'download all microdata' progr am create the complex sample survey object, using the replicate weights perform a boatload of analysis examples replicate census estimates - 2011.R connect to the sql database created by the 'download all microdata' program create the complex sample survey object, using the replicate weights match the sas output shown in the png file below 2011 asec replicate weight sas output.png statistic and standard error generated from the replicate-weighted example sas script contained in this census-provided person replicate weights usage instructions document. click here to view these three scripts for more detail about the current population survey - annual social and economic supplement (cps-asec), visit: the census bureau's current population survey page the bureau of labor statistics' current population survey page the current population survey's wikipedia article notes: interviews are conducted in march about experiences during the previous year. the file labeled 2012 includes information (income, work experience, health insurance) pertaining to 2011. when you use the current populat ion survey to talk about america, subract a year from the data file name. as of the 2010 file (the interview focusing on america during 2009), the cps-asec contains exciting new medical out-of-pocket spending variables most useful for supplemental (medical spending-adjusted) poverty research. confidential to sas, spss, stata, sudaan users: why are you still rubbing two sticks together after we've invented the butane lighter? time to transition to r. :D