DIGITAL GENDER DIVIDE DATA VISUALIZATION
The data source on the Viz is provided by “Operation Fistula”. What is “Operation Fistula” and why have they provided this dataset to the data visualization community?
Have you ever heard of “Operation Fistula”? Yes me too, “never”, like most of the readers of this article. Then I searched on the internet, “What is Operation Fistula”? I feel lucky to have internet access to search for whatever I want to learn about. As a career-oriented woman, I read for the first time about a childbirth complication that about one million women around the world suffer from. If a woman can have internet access, she would be empowered. My article is about the digital gender divide and visualization of this gap.
There are three dimensions in the data set; internet penetration among households, digital gender divide, and the gender gap to access mobile devices in percentages for 100 countries around the world. The data and article sources are #Viz5 digital gender gap and The Inclusive Internet Index.
“To be offline today means to miss out on learning and earning, accessing valuable services, and participating in the democratic public debate. The digital divide between people who have internet access and those who do not could be deepening existing gender inequalities, pushing women further to the margins of society.” — World Wide Web Foundation
INSIGHTS
Firstly, before the visualization, the correlations among dimensions have been checked. The check has helped me to explain the common increase and decrease in the gaps and internet access among households.
Mobile and internet access have similar paths among genders. so we can generalize the “technological gender gap” after adding these two gaps. If a country has a high digital gender gap, it might have a high disparity in mobile phone access. Their correlation coefficient is the strongest (+0.74) and a positive one. However, mobile phone access has a weak negative correlation(-0.49) with internet access among households. It means that in a family, both genders can have a mobile phone but not all households have internet access. Access to smartphones and affordability of mobile internet for all household matters here. Additionally, internet access disparity has a slightly stronger negative correlation(-0.61) than the mobile gap with the percentage of internet users. Therefore, some countries that have high internet penetration may have less gender gap digitally.
The next insight is about the top and bottom ranking. The largest gender gap is in Pakistan, whereas the fewest gap is in the Philippines. The internet penetration of the Philippines doubles in that of Pakistan, correspondingly about 40% and 20%. The disparity ratio is 70% in Pakistan and -14% in the Philippines.
On the other hand, the average mobile phone access gender gap is lower than the average of the digital gender divide, it has been around a 6% gap, while the average internet access gender gap is around 13%. Once more, Pakistan has been the most gender-discriminative country in terms of mobile phone access. Nevertheless, Kuwait has a 0% mobile phone access gap.
TABLEAU TIPS:
- A scatter plot was the convenient chart type for me for this visualization. Choosing this plot type makes explaining the relationship between dimensions easy.
- Additionally, in the analytics section on Tableau, clustering is possible too. The legends are different for each cluster. Also, we can drag and drop the cluster legends on the dimension box on the left.
- On Tableau, in the scatter plot, we can use customized shapes to add visual beauty to the graphs. I have practiced this trick for the mobile phone access gender gap.
- The whole dashboard image is below and you can visit the viz on Tableau Public via this link:
In conclusion, there is regional disparity among households in mobile phone access, the digital gender divide, and internet penetration according to the dataset. According to the source article, in 2020, nearly half of the world remained offline, with no access to the internet. The majority of this offline population are women in low-income and middle-income Countries (LMICs). Finally, there are some serious initiatives to cope with these disparities. Promoting women and the empowerment of women through technology forms Target 5. b in global work to achieve SDG 5 and the 2030 Sustainable Development Goals. Target 5. b seeks to: “enhance the use of enabling technology, in particular information and communications technology, to promote the empowerment of women.”.
Empowering women would make a better world.
Originally published at https://www.linkedin.com.
