Introduction

The article that I’m presenting is titled “What do men think it means to be a man?”. The article is about a 35 question survey conducted in 2018 that was filled out by 1,615 adults who identified as men. The purpose of the survey was to answer the question “What does it all mean for how men feel about being men?” (https://fivethirtyeight.com/features/what-do-men-think-it-means-to-be-a-man/).

In my opinion their question is somewhat convoluted, so I’m just going to see if “real men don’t cry”, as my grandfather used to say.

Import Data and Packages

df <- read.csv("https://raw.githubusercontent.com/samato0624/DATA607/main/raw-responses.csv")
library(DT)
library(ggplot2)
#NOTE: Here is the data for the survey questions, https://raw.githubusercontent.com/samato0624/DATA607/main/masculinity-survey.csv.

Filter to certain columns

The following questions represent the columns I’m filtering to, found in the next code chunk:
Q1 In general, how masculine or “manly” do you feel?
Q2 Do you think that society puts pressure on men in a way that is unhealthy or bad for them?
Q3 Ask a friend for personal advice?
Q4 Express physical affection to male friends, like hugging, rubbing shoulders?
Q5 Cry?
Q6 Get in a physical fight with another person?
Q7 Have sexual relations with women, including anything from kissing to sex?
Q8 Have sexual relations with men, including anything from kissing to sex?
Q9 Watch sports of any kind?
Q10 Work out?
Q11 See a therapist?
Q12 Feel lonely or isolated?
Q13 Which of the following categories best describes your employment status?
Column 14 is the survey start time
Columns 15 is the survey end time

manly_df <- data.frame(df$q0001, df$q0005, df$q0007_0002, df$q0007_0003, df$q0007_0004, df$q0007_0005, df$q0007_0006, df$q0007_0007, df$q0007_0008, df$q0007_0009, df$q0007_0010, df$q0007_0011, df$q0009, df$StartDate, df$EndDate)

Rename Columns

NOTE: For the sake of column header space I will be renaming the columns based on the list presented above.

column_names <- c("Q1", "Q2", "Q3", "Q4", "Q5", "Q6", "Q7", "Q8", "Q9", "Q10", "Q11", "Q12", "Q13", "Start_Time", "End_Time")

colnames(manly_df) <- column_names

Make a Table

Here I’m using the dt package to make a table with filters, that show 5 entries along with the base options, and has a horizontal scroll bar.

datatable(
  data = manly_df,  
  options = list(scrollX = TRUE, 
                 autoWidth = TRUE, 
                 pageLength = 5, 
                 lengthMenu = c(5, 10, 25, 50)),
  caption = "Manly Table",
  filter = "top"
)

Findings and Recommendations

The article came out sometime after the #MeToo movement and presents charts that are more geared toward understanding how men feel about their employment/workplace environment. However, I hold the opinion that their title for the article is misleading and that they are really under utilizing the data they collected. I would further explore which columns are good predictors for a mans perception of their own masculinity. You could ask questions like “Is there a correlation between self rated masculinity and the duration at which the participant completed the survey?” or “Does working out or seeing a therapist affect ones self perception of masculinity?”

Now I’m going to try to answer whether or not “real men” cry.
Answer: Approximately 1,100(~70%) men, who feel at least “Somewhat masculine”, cry rarely or more. So yes, there is evidence that “real men” cry.

# Create a bar chart with counts for each answer in the cry question and trellis based on the answers from the masculine section.
ggplot(manly_df, aes(x = Q5)) +
  geom_bar(stat = "count", width = 0.7, fill = "steelblue") +
  xlab("Q5: How often do you cry?") +
  guides(x = guide_axis(angle = 90)) +
  theme_minimal() +
  facet_wrap(~Q1)