By Eden Solarik & Indyanna Vanderlaan
Objectives
Women’s rights, particularly our rights relating to autonomy and reproductive health, are threatened worldwide. In many developing countries, women and girls lack the autonomy that is granted to their male counterparts. Since the overturning of Roe v. Wade in the US, rendering abortion no longer constitutionally protected, there has been a dramatic upset of women’s reproductive rights. (Totenberg & McCammon, 2022) While in Canada we still currently have robust protections for the reproductive rights of women, this could easily change. The Abortion Rights Coalition of Canada recently designated 100% of the Canadian Conservative caucasus as anti-choice based on their votes in the House of Commons. (ARCC Declares Conservative Caucus to Be 100% Anti-Choice, n.d.) With the Conservative party currently polling ahead of the Liberals in Canada, it may not be long before Canada is facing a tangible risk to women’s autonomy and reproductive rights. (Poilievre’s Conservatives Widen Lead over Liberals, 2024)
We aimed to illustrate the consequences of the erosion of women’s reproductive rights and autonomy to the general public using three data sets – one directly related to family-planning needs like contraceptives and one to the rates of stillbirths – representing possible consequences when those needs are not fulfilled. At the high level, we aimed for the user to consume data. Using Munzner’s scheme for task abstraction, we wanted to present the viewer with information to succinctly communicate our goal – though we do not believe the viewer will necessarily be completely unaware of this knowledge, they will not necessarily agree with the conclusions we are trying to lead them to. (Munzner, 2014, p. 47) Munzner describes that the knowledge communicated in the visualization must be knowledge that is previously known to the viewer, but this was the closest fit in Munzner’s scheme. The mid-level action we aimed to support is exploring – we wanted our user to observe the correlations between the presented variables. (Munzner, 2014, p. 54) Finally, the low-level action we aimed to support is that of comparison. (Munzner, 2014, p. 55) We wanted the user to compare countries with higher rates of satisfied family planning needs to those which have lower rates and view this alongside the other data sets. We also wanted this comparison to extend to first-world countries such as America and Canada where women’s reproductive rights are being threatened or no longer fulfilled.
Data Sets
We used two data sets from the World Health Organization: the rates of family planning needs satisfied and stillbirth rate data by country:
WHO defines family planning needs as modern methods of contraception. This data set included a range of 184 countries, a large range of years that we decided to limit to 2000-2020 due to the sheer amount of data included, and a percentage of women of reproductive age that declared their need for modern family planning methods satisfied.
The stillbirth data set included a range of 195 countries, from the years 2000-2021, and the stillbirth rate per 1000 total births in each country.
Tools
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Excel
Rationale: We used Excel as our main tool for data cleaning and organization, as well as the creation of one graph (figure 3). It was the most user-friendly option for cleaning data, as we were familiar with the software beforehand and there were many straightforward tutorials online should we need a question answered
Strengths: Excel is relatively easy to use for simple tasks, and we found the functions to be helpful for cleaning most of our data, as well as creating a simple bar chart.
Weaknesses: We were unable to figure out how to use some functions—which likely could be done in Excel—as we are not very well versed in the mathematical functions of the software.
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Tableau
Rationale: We used Tableau for numerous visualizations, both creating cursory visualizations in order to better understand our data, as well as creating some of our final visualizations.
Strengths: We found Tableau to be a powerful software with a wide range of functionality wherein we could create diverse visualizations in order to support our goals for the project.
Weaknesses: Sometimes Tableau feels overly complicated in its user interface, and changing charts manually or creating simple charts (such as bar charts) is not as easy as it is in other software such as Excel. However, we found workarounds for this.
Analytic Steps
Initially, we used three data sets – stillbirths, family planning needs, as well as the adolescent birth rate by country. The adolescent birth rate set had 198 countries and was per 1000 girls ranging from 10-14 and 15-19 years. Upon cleaning the data, however, we found the third data set was too limited, and there was very little correlation between the three.
Before performing analyses on the data, we had an idea of what our argument would be. We hypothesized that there would be a correlation between family planning needs being met and lower stillbirth and adolescent birth rates. We cleaned and organized the data, bettering our understanding of what we were working with.
Once we created cursory visualizations in Tableau, we found we hypothesized correctly for the correlation between stillbirths and family planning needs, however, it was negligible for adolescent birth rates. We discussed and since the adolescent birth rate data set was also very limited, we decided to drop it from our project.
We focused on almost exclusively forming an argument with the data visualizations. All of our visualizations were made in service of our goal to demonstrate the negative consequences that come from women’s reproductive rights being threatened. After we dropped our third data set, we fixed the scatter plot to reduce the amount of colour (as each country was assigned its own colour initially) and created the visualizations that are now in the final product.
Design Process & Principles
These are some of our first visualizations of the data:
As stated above, we chose to not inlude our third data set and fixed the amount of colour and distinct variables in the visualizations.
We wanted our visualizations to support the goals of our project – most importantly, to convince our readers that the restriction of reproductive rights is a negative thing. To do so, we needed to make clear visualizations showing the relationship between the satisfaction of family planning needs and the stillbirth rate. That is how we created Figure 2 in the journalistic story, which depicts the inverse relationship that we correctly hypothesized was present:
A key piece of the story is the differences in countries with high versus low satisfaction of family planning. We tried numerous ways to represent this data, ultimately deciding on a bar chart with a different luminance for Canada, as our story raises concerns about the direction our country could potentially go in. We included the averages of the top and bottom 10 countries for family planning needs as well as Japan and Guinea-Bissau to provide viewers with a scale to compare Canada to.
At this point, we felt that there was still something missing to tie the story together. We looked at our data together and the story thus far, and decided it may be meaningful to compare America’s rate of family planning satisfaction by year since Roe v. Wade was decided in 1973. Line graphs are one of the most effective ways to identify trends using quantitative data, so we plotted the data for America and positioned a dot to indicate 1973.
After creating this visualization, we felt our project flowed better and provided readers with a more well-rounded understanding of our thesis.
The Story
Our journalistic story starts by introducing the important issue of reproductive rights and autonomy to the reader. We explain the serious concerns for women’s rights in the United States after the overturning of Roe v. Wade and how family planning concerns relate to abortion and reproductive rights. We lay this foundation – stating that “the limitation of abortion rights is the canary in the coal mine for the subsequent restriction of women’s reproductive rights” – before beginning to visualize the data.
We use our visualizations to support the story we are telling. First, we connect family planning needs and abortion rights via Figure 1, a line chart that portrays family planning needs being fulfilled further post-Roe v. Wade. Then, we go on to visualize correlations between stillbirth rates and family planning needs satisfaction. These figures help readers to understand and connect our story with the data.
Ultimately, we introduce real concerns to our readers with data visualizations that support our claims. These visualizations establish the importance of family planning needs and how they connect to women’s reproductive rights, then how this impacts the rate of stillbirths. We end with an impactful bar graph that plots the stillbirth rates of different countries. Canada is highlighted, signalling to our audience where the nation lies and what it stands to lose when reproductive rights are threatened.
We end by summarising our key points and making a call to continue to fight for women’s reproductive rights. The story teaches our audience some of what we stand to lose should we follow in America’s footsteps and diminish the protections currently put in place.
Design Pros
Our graphs satisfy the expressiveness and effectiveness principles, encoding the most important ordered attributes (the rates of stillbirths and family planning needs satisfied) with the most effective channels (positioning). We used robust, reliable data from the World Health Organization, and backed up our claims with extensive research from reliable sources. Due to the sensitivity and complexity of the issue, we feel that a journalistic story was the best way of delivering the information to ensure that nothing was minimized or overly simplified.
Design Cons
Due to the nature of a journalistic story, there is a lot of reading that viewers must do in order to understand our project, though we tried to keep it as succinct as possible. Our visualizations alone also cannot capture the nuances of this topic, meaning they may appear overly simplified. Without the added context, viewers may be unable to understand fully or come away with any significant insights.
These data sets also lacked information from more recent years (2022 and 2023) so despite our story being largely to do with recent developments, we were unable to show data closer to this year.
References
ARCC declares Conservative Caucus to be 100% anti-choice. (n.d.). Abortion Rights Coalition of Canada. Retrieved 1 March 2024, from https://www.arcc-cdac.ca/conservative-party-anti-choice/
GHO | By category | Adolescent birth rate—Data by country. (n.d.). WHO. Retrieved 1 March 2024, from https://apps.who.int/gho/data/node.main.REPADO39?lang=en
GHO | By category | Catastrophic out-of-pocket health spending (SDG indicator 3.8.2 and regional indicators where available)—Data by country. (n.d.). WHO. Retrieved 1 March 2024, from https://apps.who.int/gho/data/node.main.UHCFINANCIALPROTECTION01?lang=en
GHO | By category | Family planning needs satisfied—Data by country. (n.d.). WHO. Retrieved 1 March 2024, from https://apps.who.int/gho/data/node.main.FAMILYPLANNING?lang=en
GHO | By category | Stillbirth rate—Data by country. (n.d.). WHO. Retrieved 1 March 2024, from https://apps.who.int/gho/data/view.main.STILLBIRTHv?lang=en
Munzner, T. (2014). Visualization analysis and design (0 ed.). A K Peters/CRC Press. https://doi.org/10.1201/b17511
Poilievre’s Conservatives widen lead over Liberals: Nanos. (2024, February 21). CTVNews. https://www.ctvnews.ca/canada/poilievre-s-conservatives-widen-lead-over-liberals-nanos-1.6777766
Totenberg, N., & McCammon, S. (2022, June 24). Supreme Court overturns Roe v. Wade, ending right to abortion upheld for decades. NPR. https://www.npr.org/2022/06/24/1102305878/supreme-court-abortion-roe-v-wade-decision-overturn