The role of social class and gender in the sinking of the Titanic

First-class passengers on the Titanic were more than twice as likely to survive the disaster than those in third class

 
A JSTOR Daily article by Nashwa Khan published in 2016 titled "What the Titanic Reveals About Class and Life Expectancy" discusses the link between socioeconomic status and the lower survival rate for third-class passengers aboard the Titanic. The article highlights how as a passenger's socioeconomic status declined so did their likelihood of survival. The article suggests using the event of the Titanic sinking as a lens to help analyze the relationship between socioeconomic status and life expectancy. 

An article written by Mark Carrigan published 2012 titled "Social Class and Life Chances as seen through Survivor Rates on the Titanic" also talks about the role of class for the passengers.  Carrigan emphasized how the class system in 1912 was extremely rigid and shaped the outcome of passenger survival. Carrigan also criticizes the poor design of the ship for contributing to poor survival rates due to the lack of lifeboats on board the ship. 

An article by Wayne Hall published in 1986 titled "Social Class and Survival on the SS Titanic" examines key factors that influenced individuals' survival aboard the Titanic such as sex and social class. Hall discusses the Mersey inquiry which had a committee examine the events of the sinking. According to the Mersey inquiry and Hall, there were three possible determinants as to why social class played a pivotal role in one's survival. The first theory was that third-class passengers were intentionally restricted from gaining access to a lifeboat. The second theory is that the way in which the Titanic was operated was not favourable for third-class passengers. The third theory is that third-class passengers are responsible for their lower life expectancy due to the way they conducted themselves during the incident. Aside from these three theories, Hall also mentions how the location of the lifeboats may have also played a crucial role in survival as they were located near first and second class passengers areas making it difficult for third-class passengers to access.

Hall revealed that women had a higher survival rate because of policy. According to Hall, overall the policy was adhered to however, some crew members who were in charge of filling the lifeboats were more lenient than others and let several men into the lifeboats. Therefore, due to this policy women (and children) were given priority seating in the lifeboats. However, not all women were equally prioritized which resulted in 51% of third class women dying. 


Passengers embarked from Southampton, England; Cherbourg, France; and Queenstown, Ireland (now Cobh). Since Cherbourg embarked with the most first-class passengers, Cherbourg had a higher survival rate of 56%. Moreover, since Queenstown embarked with the most third-class passengers, Queenstown passengers had a lower survival rate of 36%.


Does all this mean that a first-class woman who embarked from Cherbourg was guaranteed to survive the fatal incident? No, however, she would have had a much more significant survival probability than a third-class male from Cherbourg.

A 2012 article by Bridget Diamond-Welch titled "A Nightmare of Titanic Proportions: Social Class & A Ticket to Ride" contends that during the events of the Titanic, social class and gender played a role in one's survival. However, Diamond-Welch argues that social class still significantly influences the quality of life and life expectancy for many around the world. For example, wealthier people have better access to health care and resources such as clean air and water. She also discusses how infant mortality rate is significantly higher in lower-income and middle-income countries compared to higher-income countries.

Although the events of the Titanic happened over 100 years ago, the determinants of survival are similar today. People are still limited and restricted based on the social class they are born into which greatly impacts their quality of life and may even contribute towards their death.   

Data Update #3

1. Datawrapper Charts

2. Unanswered Question

What was the survival status of all people aboard the Titanic?

I currently cannot answer any questions regarding the crew or staff that were aboard the Titanic. The dataset I am using only includes information on passengers that were aboard the Titanic. Consequently, there is no information for any crew or staff members that were aboard. Therefore, if I wanted to ask a question regarding the survival status of all those aboard the Titanic I would be unable to do so.

3. The Dataset I need

The dataset I need to answer the questions above would have to contain all information regarding the crew/staff aboard the Titanic. The dataset I am currently using is based on data collected from Encylopedia Titanica's records. Encylopedia Titanic does have a complete database that includes information for both the passengers and the crew however it is only available with the purchase of annual membership of £10.00. I would initially attempt to contact the organization through their webpage explain my reasoning for wanting the data and ask for access to their database for free. Alternatively, if this were to fail I would pay the £10.00 for access which is equivalent to approximately $18 CDN.

Other questions I could ask if I were able to obtain this data:

• What percentage of crew members survived?
• What is the difference in survival for passengers vs. crew?

Data Update #2

Lead

When the RMS Titanic sank in 1912, 62% of the first class passengers survived while only 25% of the third class passengers survived; this suggests that the socioeconomic status of the passengers played a major role in their final moments aboard the Titanic.

Excel Workbook: Raw Data & Small Slice

My excel workbook is divided into two different sheets: the original raw data and a smaller slice. The smaller slice of data shows the total number of passengers in each class divided into two different coded categories: 0 for died and 1 for survived. Below the total is the share of survived passengers for each class which is the percentage of each class's survival rate.

Original Data Set

The original dataset can be found here. The main source of information for the dataset is from the Encyclopedia Titanica. 

Supporting Article

A JSTOR Daily article by Nashwa Khan published on June 2, 2016 titled "What the Titanic Reveals About Class and Life Expectancy" discusses the link between socioeconomic status and the lower survival rate for third class passengers aboard the Titanic. The article highlights how as a passenger's socioeconomic status declined so did their likelihood of survival. The article suggests using the event of the Titanic sinking as a lens to help analyze the relationship between socioeconomic status and life expectancy.

Data Update #1

1. What dataset will you use for your final report?

The dataset I will be using for my final report is the passenger manifest from the RMS Titanic. The Titanic dataset includes a variety of information about the passengers aboard the Titanic. It is important to note that this dataset does not include any information about the crew of the Titanic.

2. Describe the dataset. What kind of data does it contain?

The dataset contains information regarding passengers' names, sex, age, fare (British pound), and passenger class. The dataset also has information on whether or not the passengers survived the fatal incident. Other information that is included for some but not all passengers is ticket number, home destination, cabin, boat number, and body identification number.

3. Is there anything about your data that you don’t understand? (i.e.
what a column heading means). How will you find this out?

There were two variables that I was unable to understand at first. One column heading was titled sibsp and another column heading was titled parch. However, I was able to find a key to the dataset that provided variable descriptions. Sibsp is the number of siblings and/or spouses aboard the Titanic and parch is the number of parents and/or children aboard the Titanic.

4. What are some questions you hope to answer with your data? List at
least three. (you don’t need the answers at this point)

There are a few questions I would like to answer with this dataset:

• What is the percentage of women versus men that survived? 
• Which passenger class had the highest survival rate? Which passenger class had the lowest?
• Of the cities from which passengers embarked, which had the highest survival rate? Which city had the lowest?
• What was the percentage of first-class women versus third-class women that survived? Compare to the percentage of survival for first-class and third-class men.
• How many passengers had siblings or spouses aboard with them?
• How many passengers had parents or children aboard with them?

Data Visualization Analysis

Statistics Canada released this visualization December 2017 showing Employed labour force who worked full year, full time and reported employment income in 2015.  The visualization is concisely designed, comprehensible, and visually appealing, but it does not provide the information in the clearest way possible. The pie chart was a poor choice to display the collected data because there are too many individual slices of the chart. In addition, the visualization relies on its core center to provide information instead of focusing on its interactive portion. The slices of the pie chart would be meaningless without the core center.  Moreover, the occupation titles appear on some of the categories but they are cut off and not fully legible. The incomplete titles cannot be fully seen unless they are clicked on.

The visualization can be filtered by using the drop-down menu to select National Occupational Classification (NOC), Highest certificate, diploma or degree, or, by Geographical location to provide more specific information. 

The list that the drop-down menu provides for the NOC is extremely long and tedious to scroll through.

The visualization could have been simplified if there was less data represented. The pie chart that shows the total occupations is an overwhelming image and does not make sense if the numbers were removed. Once a more specific category is selected the visualization is improved and simplified because there is less to look at. However, even the simplified chart is poorly constructed because the rings would not make sense without the core center providing numbers.

The visualization has too much information for it to work in this format. Some of the slices in the pie chart are so small that it is easy to pass over them. For example, the Architectural technologists and technicians category is barely visible. This visualization would work better as a series of bar charts broken down by field of occupation. If the charts were displayed as bar charts the information would be clearer to interpret with or without showing numbers.

The interactive portion of the visualization was its strongest element. It was easy to maneuver and simple to understand. The visualization was accessible to interact with either by using the drop-down menu to refine the search or by scrolling over the different slices and clicking on one to learn more information. The biggest critique is that the amount of information the visualization is attempting to provide is does not display well in pie chart format.

Source: Employed labour force who worked full year, full time and reported employment income in 2015, 2016 Census (Table). http://www12.statcan.gc.ca/census-recensement/2016/dp-pd/dv-vd/occ-pro/index-eng.cfm

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