Introduction
There has been quite a few maritime disasters in the past. Although these disasters, represent a scar of saddness in history, there is much to be learned from these events. There are 18 ships within a ship data set that we can look at closely and compared the data. From this data, we may be able to draw some conclusions as to how social norms impact the survival in maritime disasters and how social predictors can attribute to survival rates. The event that occurred on the RMS Titanic provided a substantial amount of information for analysis and comparison. From the data, it is apparent that aboard the RMS Titanic, there was a disparity among age, gender, social class, crew and passengers. Although each maritime disaster was unique, there were many similarities among them. These similarities point to specific information that reveals the role that societal behaviors play and how it can potentially effect the chances of survival.
Background
The RMS Titanic is used as the basis for comparison. The RMS Titanic was a British passenger vessel. The Titanic was supposed to make sail for New York from Southhampton. On April 10, 1912 the RMS Titanic began it’s journey. The jounrey to New York was interrupted because four days after it left Southhampton, the ship collided with an iceberg in the middle of the North Atlantic Ocean. It took a little less than two hours for the RMS Titanic to sink. The RMS Titanic carried 2,224 passengers and crew. The deaths totaled more than 1,500 and only about 705 people survived. This Vessel gives a substantial amount of evidence that the way people react in maritime disasters can effect the amount of people that survive. Social norms and behaviors can serve as predictors as to survival rates in maritime disasters. Since the RMS Titanic had many variables that can be examined to draw conclusions for the future. ## My Ship History and Details
The SS Princess Alice was also a disaster caused by collison. The SS Princess Alice was a passenger steamer and it would make route trips between Swan Pier and Gravesend and Sheerness. In 1878, the SS Princess Alice collided with the Bywell Castle. It is not very clear as to how many passengers and crew were aboard the SS Princess the day of the disaster. However, according to wikipedia, “over 605 people died and between 69 to 170 people were rescued”. Unlike the RMS Titanic, the SS Princess Alice sank within 4 minutes. Aboard the SS Princess Alice, there was no social class structure or Women and Children First (WCF) Order. ## My Ship Compared to Other Ships in the Disaster Data
Since we have a good amount of information from the RMS Titanic, we are able to compare other maritime disasters such as the SS Princess Alice to the Titanic. Comparing the SS Princess Alice to the RMS Titanic, we can assume that the social class structure and a WCF order made a difference on the chances of survival. However, comparing these two disasters is not enough to support a hypothesis on social norms and societal behavior effects on survival rate. By taking a further look into other maritime disasters we have a larger sample and can better compare the characteristics that attribute to survival rate. The SS Princess Alice is one disaster that can be considered typical when comparing it to the other ships in our ships data set.
plot3<-ggplot(ships, aes(x=`Cause`,y=`No. of passengers`))
plot3+geom_boxplot()
These box plots present each type of disaster that effected the ships in the ship data set. The SS Princess Alice was destroyed by a collision. Collision has the largest range of ships that were afflicted by this cause. The SS Princess Alice is among the most common cause of disaster. Also, when the cause of disaster is compared to the number of passengers, the SS Princess Alice ranges close to the median. This means that the SS Princess Alice may be a typical case within passenger size and cause of disaster.
Theory and Hypotheses
The information that is given presents many questions. If we look at the SS Princess Alice as being a typical case among maritime disasters, then we can examine a few hypotheses. By examining different variables and comparing them to each other we can see what variables may effect the survival rate. According to Elinder and Erixson, “previous research on the Titanic has found, in line with the notion of WCF, that women have a survival advantage over men, whereas evidence from the Lusitania disaster indicates no difference in survival rates between men and women”. The authors suggest that the presence of a WCF order can create a disproption in which, a female’s chance of survival is higher than a male. Also as seen with the RMS Titanic data, social class structure played a role in survival. Since there was no social structure or WCF order on the SS Princess Alice, I hypothesize that the chance of survival is decreased based on gender. Elinder and Erixson also examined the survival rates of the crew variable on the 18 different ships. “Crew members are familiar with the ship, often have emergency training, are likely to receive early information about the severity of the situation” (Elinder and Erixson). The social class structure on the SS Princess Alice was not apparent however, there is data available for the crew aboard the ship. If we take into account what the authors are stating about crew survival, I hypothesize that aboard the SS Princess Alice, if a passenger was a part of the crew, their chances of survival is increased.
Data
crosstab(RMS_Titanic, col.vars = "Survival", type = "c")## Survival %
## 1 0 67.8
## 2 1 32.2
## 3 Sum 100.0crosstab(RMS_Titanic, col.vars = "Crew", type = "c")## Crew %
## 1 0 59.6
## 2 1 40.4
## 3 Sum 100.0crosstab(SS_Princess_Alice, col.vars = "Survival", row.vars = "Crew",type = "c")## NA NA NA NA
## 1 Survival 0 1
## 2 Crew
## 3 0 96.7 92.7
## 4 1 3.3 7.3
## 5 Sum 100.0 100.0The first univariate table shows the percentage of survival among the passengers on the RMS Titanic. The second univariate table shows what percentages of the people aboard the RMS Titanic were a part of the crew. Here we see that the survival rate on the RMS Titanic was 32.2% and the crew accounted for 40.4%. In the bivariate cross tabulations, the table shows the differences between gender and crew. The tables describes the percentages of men that were also a part of the crew and the percentages of women that were a part of the crew of the total amount of people aboard the RMS Titanic.
crosstab(SS_Princess_Alice, col.vars = "Survival", type = "c")## Survival %
## 1 0 80.2
## 2 1 19.8
## 3 Sum 100.0crosstab(SS_Princess_Alice, col.vars = "Crew", type = "c")## Crew %
## 1 0 95.9
## 2 1 4.1
## 3 Sum 100.0crosstab(SS_Princess_Alice, col.vars = "Survival", row.vars = "Crew",type = "c")## NA NA NA NA
## 1 Survival 0 1
## 2 Crew
## 3 0 96.7 92.7
## 4 1 3.3 7.3
## 5 Sum 100.0 100.0Here the first univariate table shows the percentage of survival among the passengers on the SS Princess Alice. The second univariate table shows what percentages of the people aboard the ship were a part of the crew. The survival rate on the SS Princess Alice was 19.8% and the crew accounted for 4.1%. In the bivariate cross tabulations, the table shows the differences between gender and crew. The tables describes the percentages of men that were also a part of the crew and the percentages of women that were a part of the crew of the total amount of people aboard the SS Princess Alice. If we compare the SS Princess Alice’s gender and crew data against the RMS Titanic, both survival rates were lower versus survival. Between both ships the crew accounted for a smaller portion of passengers.
results<-glm(Survival~Crew + Gender, data=RMS_Titanic, family = binomial(link = logit))
coef(results)## (Intercept) Crew Gender
## -1.4541904 0.2107338 2.4520885results<-glm(Survival~Crew + Gender, data=SS_Princess_Alice, family = binomial(link = logit))
coef(results)## (Intercept) Crew Gender
## -1.3344110 0.7200461 -0.6315836Within the results of the GLM for the RMS Titanic, it shows that gender, representing females had a positive effect on survival. The GLM results for the crew on the RMS Titanic was small. Therefore, survival according to crew was small. However, within the results of the GLM shows that gender, representing females, on the SS Princess Alice may have had a negative chance for survival because the coefficient is negative. The Crew coefficient suggest that being a part of the crew had a positive effect on survival.
# Results
We know that the SS Princess Alice sank quickly, where as the RMS Titanic took longer to go down. We can see that on the following box plot chart, the box plot that represents survival is larger than the box plot that represents non-survival. The SS Princess Alice is not typical in this instance but the RMS Titanic is.
plot1<-ggplot(ships, aes(y=`Name of Ship` , x=`No. of passengers` ))
title1<-ggtitle(" Ships and Passengers")
plot1 + title1 + geom_point()
plot1 + title1 + geom_point() +geom_segment(aes(yend = `Name of Ship`), xend = 0, color = "grey50")
quartile1h <-
geom_hline(yintercept=quantile(ships$`No. of passengers`, probs=c(.25),
na.rm=TRUE), color="green", linetype="dashed", size=1)
quartile2h <-
geom_hline(yintercept=quantile(ships$`No. of passengers`, probs=c(.50),
na.rm=TRUE), color="red", linetype="dashed", size=1)
quartile3h <-
geom_hline(yintercept=quantile(ships$`No. of passengers`, probs=c(.75),
na.rm=TRUE), color="blue", linetype="dashed", size=1)
plot3<-ggplot(ships, aes(x=factor(Survived) , y=`No. of passengers` ))
plot3+geom_boxplot()+quartile1h+quartile2h+quartile3h+ggtitle("Survived")
If we look into how quick the ships sank, we can see that the SS Princess Alice was a typical case because it is very close to the median.
plot4<-ggplot(ships, aes(x=factor(Quick) , y=`No. of passengers` ))
plot4+geom_boxplot()+quartile1h+quartile2h+quartile3h+ggtitle("Quick")
Since the SS Princess Alice sank so quickly, there was never a WCF ordered. This could account for the fact that gender played a role in survival chances. On the RMS Titanic, the ship sank slowly, therefore there was time to issue a WCF and this can explain how the gender coefficient is positive. When we look into the crew data for both ships, we see that on the SS Princess Alice where there was no social class difference, the survival rate was higher than the Titanic. The divison of social class on the RMS Titanic contributed to the low survival rate of the crew.
Conclusions and Future Research
The RMS Titanic disaster provided information for data analysis on maritime disasters. There were many characteristics that can be examined in order to draw conclusions on how societal behavior and social norms contrbuted to survival. The variables examined included the number of passengers, gender, social class, and crew. Using the RMS Titanic data as a basis for comparison, each variable can be compared with other maritime disasters. For instance, according to the data, the SS Princess Alice is a typical case. In the case of the SS Princess Alice, the cause of disaster was the same as the RMS Titanic. However, unlike the RMS Titanic, the SS Princess Alice did not have a distinction between social class and a WCF order was not issued. Social class structure did contribute to survival on the RMS Titanic and the high percentage of female survivors can be accreditted to a WCF order. The crew aboard the RMS Titanic had a lower percentage of survival compared to the separation of social classes. Apparenly, without a social structure, the crew has a higher percentage of survival. These two differences between the RMS Titanic and the SS Princess Alice may be due to the amount of time each ship took to flounder. The RMS Titanic took about 2 hours to sink, which gave enough time for a somewhat organized evacuation. Thereby, a Women and Children First (WCF) order could have been initiated. We can assume the crew of a ship is very knowledgeable and may have had training for emergency evacation. Therefore in a case like the SS Princess Alice, where the ship sank within 4 minutes, it can be highly likely that the crew members have a higher percentage of survival. Looking at the data, aboard the SS Princess Alice chances of survival were greater if you were apart of the crew. There are similarities however, a combination of variables may project the same results. Therefore when analysizng the ship’s data, it is important to examine them individually because there are different variables that may effect disasters differently. Additional future should be conducted on ships that are younger. The RMS Titanic and the SS Princess Alice were ships that were built over 100 years ago. Any disasters that have occurred in the last 50 years should be compared to the older ones such as the RMS Titanic and SS Princess Alice. Comparing newer ship disasters to the old ones can help substantiate the hypotheses proposed by Elinder and Erixson.
References
Elinder, Mikael and Oscar Erixson. 2012. “Gender, Social Norms, and Survival in Maritime Disasters.” Proceedings of the National Academy of Sciences 109(33):13220-13224. Retrieved October 19, 2016.
Wikipedia. 2016. “RMS Titanic”. Wikimedia Foundation. Web. Retrieved December 12, 2016. https://en.wikipedia.org/wiki/RMS_Titanic
Wikipedia. 2106. “SS Princess Alice (1865)”. Wikimedia Foundation. Web. Retrieved December 12, 2016. https://en.wikipedia.org/wiki/SS_Princess_Alice_(1865)