The Albany militia 1760 dataset is a composite dataset. It includes textual numeric and geographic types of data. The geographic part of my data is the birthplaces of each individual. These birthplaces are in a single column in the data chart. Most of the men on the militia roster are from European countries. As in most cases ones complexion combined with other physical traits can be used to pinpoint ones origin. Being able to find out where someone’s ancestors are from is classified as geographic data in my eyes. Therefore I hesitantly include this point.
As stated there is a numeric aspect to my data contained within columns one and five. The numeric data would be the age and height of the militia men. The age of the men recruited is actually very important. People who are experienced can make organizing zealous younger recruits easier, at the same time, older men with no experience may find it harder to pick up new skills once enlisted in the militia.
The rows of my data set are quite archaic in nature. There is no particular purpose to them besides the fact that columns and rows are needed within the table. It is possible that whomever was recording this data simply listed people information as they showed up. This data could utilize the rows in more sophisticated ways such as listing off the names in alphabetical order. This would make the data much more pleasant to look at. Not a single row corresponds to a column in a way that makes it organized.
With slavery still being a thing at this point in time, the 1760 Albany militia dataset was shocking due to the sheer number of colored men that were enlisted. Upwards of 43% of the men listed were people of color. With slavery still being a thing, cowardly slave owners had the option to send their slaves to the front lines in their stead. This way they would be contributing to the militia efforts.
Textual data comes into play when the companies and commanding officers are observed. The militia can’t have a large mob of people running into battle. This would be extremely inefficient. As previously stated the rows of this graph are relatively useless. That being said the columns make it simple for someone looking at this data to find the location of an individual after some searching for their name.
This dataset covers the years 1760 to 1763. The American Revolution started in 1763 making the fact that this dataset cuts off at the start of the revolution interesting. The data stopped being recorded because at that time it is unlikely someone can keep track of all these men and potential recruits in the midst of constant fighting and travels. Also based on the time frame of the data it can be inferred that the data recorded is preparation for the impending war
My first graph takes a look at the migration patterns into Albany. My looking at the homelands for each individual it becomes apparent that most of the people getting ready to fight in the American Revolution are originally from a foreign country. The number of “home grown” Americans makes up a solid forty three percent. That makes it so more than half of the people in the militia are not native to this land. This graph also shows the occupation of each person. Not a single one of these people were labeled as a soldier. These people went into the militia not knowing anything about combat. This graph is set to calculate a moving average of age. The ages of these men are mostly in their twenties with very few men in their 40’s. Out of pure speculation, since most of these people came from overseas they obviously had a problem with how something was being run over there. These people enlisting was a way for them to protect the idea of stereotypically “pursuing the American dream” It is interesting to notice that out of the occupations listed no one was a type of nobility. Not a single person could be considered high ranking. These people were mostly your common laborers. With most of the people who came here being of a humble background (labourers, blacksmiths. Etc.) This made it easy for a sense of comradery and community to form.
My second graph takes an odd approach. I was curious as to whether or not there would be some kind of racial divide within the militia. Therefore i took the complexion of each person and combined it with the data of each company. This allowed my graph to show me how many people of each race there was. Personally i believe my graph is misleading. I would have liked to have each company split up to show the divides but the way it is currently illustrated it can be misconstrued. The number of dark or negro men within the militia was unexpectedly high. They made up the highest concentration of one race withing the entire militia with over two hundred thirty men. Colonists and Indians were on pretty good terms but I never expected someone of native american origin to be directly placed in the militia. From my knowledge of tribal culture they would assist but would make it very clear that they were their own entity throughout the entire ordeal. For one to be in the militia shakes the foundation of the common understanding of Native American culture at that time.
My choice of graph is called a side by side circle graph. This graph originally used circles to illustrate the data presented but I found that using squares gives it a different effect. By using squares which are made of straight lines the mind is able to extend the lines making it seem as though there is a horizontal bar graph. I attempted to use a horizontal bar graph but I found that there were too many bars to clearly see what was happening. Also the length of the graph was absurd.
My original color scheme was supposed to go along with the complexions that are listed within my data I thought that it would make it easier for anyone looking at it. Not only did this choice backfire because the colors made the graph very unattractive it also strained the eyes to look at.
This graph supports my points about people being forced out of their countries by internal factors. Immigration is clearly very high at this point in time. People don’t migrate in mass without a sufficient reason. Unfortunately there was no religion based data in the selected dataset. This data would have been useful due to religious persecution of Catholics and Jews was on the rise as the protestant religion gained power in Europe. According to this graph Irish immigration was extremely high even when compared to other areas on the graph. The main religion of Ireland is Catholicism and with catholic persecution rising it makes sense that migration also increases.
My second choice of graph is a packed bubble graph. This graph is more intricate than the other one because everything from the size of each bubble to the color means something. Based on this graph each company seemed to be made up of one major ethnicity. In one location this graph shows that the concentration of people of color is higher than any other ethnicity there. This makes it quite sad that at this time slavery is still in effect.
Within the soldier count on each bubble there is an uneven distribution of man power with one company actually having 1 person. This may be misleading data due to the officer they report to not being listed on this graph. When I tried to add this in the graph became severely distorted to the point I couldn’t make heads nor tails of what I was looking at.
The colors for this graph were selected purely on the basis that they are easy to look at. Even though they are easy to look at, the colors do a good job of making each area stand out on its own.
Thing’s I’d like to know
I would like to know about the different religions the people who came to Albany practiced. With the information on how many people of each religion came, I would be able to find out exactly how powerful the oppressive institutions were. As stated in multiple locations the protestant church was gaining power. I would be able to essentially give the church a power ranking so to speak.
My data directly overlaps with the protestant rise to power in Europe. The data presented also directly overlaps with the time period where Britain was extremely strong in comparison to the countries around it. Great Britain was in control of a large amount of land. They had stakes in Ireland, Germany, and most other European nations. After the reformation in 1534 Britain became protestant. By the early to mid-1700’s pressure is being applied to the citizens of various nations trying to get them to convert. The quality of life in these nations was also quite poor. People were forced to pay high rent to Britain in order to keep their land. This forces people to make sacrifices usually of the food variety. With people starving and religious tensions at a high people had two options. These options were to set out to America and attempt to start anew or bear with their current situation and hope that it gets better.
Another point of reference: based on what I stated above Britain was applying pressure outwardly on all the nations around it, But at the same time people are leaving England in large amounts. The English implemented a new sanction called inquisitions. These inquisitions were derived from the Spanish version where they took a lot of land. This made it so borrowing money from an English bank was placing your head on the proverbial chopping block. The inquisitions allowed for the English to confiscate your land in order to clear your debt. Once a man’s land was taken his life was effectively over. This made leaving for America a lot easier.
Power was shifting in the Americas and also in Europe.The Seven Years’ War ends. Britain, Spain and France sign the Treaty of Paris and Austria and Prussia sign the Peace of Hubertusburg in February. Austria gains nothing. France loses possessions in the Americas and cedes to Spain the huge territory of Louisiana, including New Orleans. France agrees to pull out of India, and it cedes its colony by the Senegal River to the British
Credit to: http://www.fsmitha.com/time/ce18-7.htm