This dataset contains information on the admission of people to Easter State Penitentiary. It includes the name, age, ethnicity, religion, birthplace, prisoner number, admission and discharge dates, offense, sentencing date and location, number of convictions, as well as several notes about the inmates. The dataset contains information about convicted criminals. The data itself is a mix of qualitative and quantitative data. The sentence length is an example of quantitative, while the offense description is qualitative. The data spans 13 years, from 1830 to 1843. Geographically speaking, it covers the Northeast United States. The scope of this data only includes convicted criminals, not the entire crime rate. This specific data shows the types of crimes committed in this region during this time period, as well as the demographics of the offenders. This data cannot show the same trends in other areas and over other time periods. It also can’t show whether the rate of crime has changed at all since earlier time periods.
A majority of the information comes from the admission records of the prison. There was also some information pulled from a report made from investigating the running of the prison. Some of the notes on the inmates were observations made by the prison’s Moral Instructor, Thomas Larcombe. These were observations about the moral states of the inmates. Information for the dataset was also pulled from letters to, from, or between the inmates.
The dataset is set up chronologically by admission date, starting with March 1830 and ending in May 1843. Each individual row contains the data for a single inmate. The columns are divided into specific information about each individual, such as their age or offense. This is likely to make it easier to compare specific data about the individual inmates. If this was the only dataset used, there would be a lot of information left out. For example, the goal of the prison was to reform the inmates, but the discharge notes don’t say whether or not that goal was reached. It also leaves out information regarding the time spent in the prison. For example, the inmate’s behavior and if or how many times they were disciplined. The data is also biased towards the prison administrators, specifically the notes about the inmates. Much of the information was recorded by the prison workers, so we’re seeing it through their observations. If this was the only dataset use, it would also leave out similar information for different time periods and areas in the United States.