Black Dyke Mill

Throughout history, the experiences of ordinary people are often neglected and forgotten. However, it is exactly the ordinary people who form the details of the history, and their experiences could show relations to our own lived experiences. Through referring to specific historical materials, it is possible for us to learn about life conditions of workers at that time. In the collection of the spinners’ wage book, we could access data including worker names, the amount of wage, and dates of paying wage in the Black Dyke Mills, during the time period from August 1828 to January 1841. Among the many subjects which could be focused on, we choose to approach this collection from the perspective of ordinary workers’ lives, and further extend to the topic on data privacy which could relate to our own lived experiences.
In this collection, the names of workers at list and their paid wage per week are thoroughly recorded. Basing on these data, we could calculate the number of workers at work and their average wage within a certain time period. Though these two variables are constantly changing, we discovered from an annotation in the collection that in 1835, the factory went through structural transformation on a large scale. Therefore we decided to apply data visualization to worker numbers and average wage between the time period of 1834 and 1836, to see how the transformation of the factory affected the life conditions of the workers. Research questions include: What are the changes in the number of workers at work and their average wage between 1834 and 1836? Are there any connections in them, and what do they reflect? According to the changes in the purchasing power of British pound, what are the life conditions of spinner workers at that time, comparing to modern British workers?
In this collection, we noticed that a worker named Andler James (supposed to be female according to the librarian) continued to work in the factory between 1838 and 1840, therefore we decided to trace her wage changes in this period, to see what we could discover. Research questions include: What are the wage changes of Andler James between 1838 and 1840? How is her wage level comparing to the average wage of spinners in 1830s’ Britain? What does this reflect? At last, we decided to reflect upon the topic of data privacy according to this collection. These data which contain names and wage information are undoubtedly personal privacy, but their existence do help us a lot in understanding historical conditions. Considering this dilemma, we choose to conclude our research by questioning ourselves: What could we learn about the relationship between data privacy and data analysis?
Through manually scraping data from the collection, we got several datasets basing on our research questions. Our first two data visualization graphs show that the largest fluctuation for the number of workers at work and their average wage between 1834 and 1836 happened in 1835 when the factory went through structural transformation. Through combining these two graphs together, we found that the number of workers and their average wage are in a negative correlation. After some research, we came up with two assumptions: The first is that the factory demand did not grow as fast as the production rate, and the second is that the workers tend to decrease efficiency when there are more people at work. Then, through comparing the purchasing power of British pound in the 1830s and today, we found that the average wage of these spinners, which was approximately 5.23 shilling per week, only equals about 43.4 pound today, which is a comparatively low number. This shows that many spinners in the 1830s have low income and lived a hard life.
Next, through scraping the wage of Andler James between 1838 and 1840, we made another visualization graph which shows that her average wage equals approximately 4.5 shilling per week. This is way less than the average wage in 1830s Britain, which is 14 shilling, even less than the average wage of spinners that we found out above. After more research, we supposed that this is related to the stereotypical image for female workers at that time, which considers them as more tolerant about work and could stand lower salaries. This also shows that wages at that time vary widely even in the same industry, and the factories tend to squeeze their workers, resulting in hard working and living conditions for ordinary workers.
Through this research, we gained some insight into social situations and living conditions of ordinary workers in 1830s Britain. Though at first sight, these data only contain unfamiliar names and wage amount, there are measures to make them narrative. The chance of accessing historical data is rare and valuable, comparing with accessing data in modern society, since the collection and analysis of data have become simpler. We would need newer moral frameworks for dealing with all kinds of data around us, so as to maintain the potential of narrative data.
What's more, since we consider individual private infomation are unnecessary in data analysis, we created several pictures that blurred names and eyes. In addition, we used AI, gave them a paragraph which illustrate the circumstance of workers, then the AI generated several pictures with imagination, which their faces are also blurred. We thought both those fancy tries reveal that private infomations are important and should be protected by laws, they are not useful and should not be used in modern data analysis.