Maternity and Race

This week for ICM I wanted to illustrate statistics for the problems women face, and I wanted to do it in a way that helps viewers understand the issues women of colour or lower education attainment face, and also make it easier to understand and visualise — using emojis of course.

I imported the data in a .csv file from https://mchb.hrsa.gov, HRSA for Maternal and Child Health, and read up on of their surveys done in 2015 for maternity leaves taken in the US, divided by race, educational attainment and reasons for not getting or taking the leave.

Maternity leave from employment after childbirth provides critical time for maternal-infant bonding and adjustment to life with a new baby. Longer length of maternity leave is associated with increased breastfeeding duration, as well as improved maternal mental health and child development. The WOMEN’S HEALTH USA 2011 stated that “the Family and Medical Leave Act (FMLA) guarantees both women and men up to 12 weeks of unpaid leave around the birth or adoption of a child as long as they work for larger employers (50+ employees) and meet certain tenure and working hour requirements.” However, many women cannot afford to take unpaid leave and usually use a combination of short-term disability, sick leave, vacation, and personal days in order to have some portion of their maternity leave paid. The U.S. is one of only 5 countries in the world that does not mandate paid maternity leave.

According to their study:

In 2006-2015, 66.0 percent of women reported being employed during their last pregnancy, of whom 69.7 percent reported taking maternity leave. Thus, nearly one-third of employed women did not report taking any maternity leave (30.3 percent). Women with at least a college degree were more likely to have taken leave than those who had attended college but not graduated (80.0 versus 71.6 percent, respectively) while less than half of women without a high school degree reported having taken leave. Hispanic and non-Hispanic Black women were less likely to report having taken maternity leave than non-Hispanic White women (62.5 and 64.3 percent, respectively, versus 72.2 percent). When taken, the average length of maternity leave was 10.0 weeks (data not shown). Among employed women who did not take maternity leave for their last pregnancy, 5.1 percent did not take it because it was not offered or allowed by their employer. Of non-Hispanic White women, 3.2 percent reported this reason, compared to 8.2 percent of Hispanic women and 10.2 percent of non-Hispanic Black women.

I graphed these using skin colour as a major visual tool to tell the difference between the treatment of women at work.

Below are the visualisations and my code:

 

The key: (will be added to the sketch later)

Women who took maternity leave based on race

Employer’s disagreement on maternity leave based on race

Women of (presented) colour who enrolled in college

Educational Attainment levels:

Less than High School

High School

Some College

Bachelors Degree and higher

CODE:

let dataRace;
let dataEducation;
function preload() {
dataRace = loadTable(“race.csv”,
“csv”,
“header”);
dataEducation = loadTable(“education.csv”,
“csv”,
“header”);
}
function setup() {
createCanvas(430, 400);
console.log(dataRace.getRowCount());
console.log(dataRace.getColumnCount());
white = loadImage(“maternity/white.png”);
black = loadImage(“maternity/black.png”);
hispanic = loadImage(“maternity/hispanic.png”);
mixed = loadImage(“maternity/mixed.png”);
e1 = loadImage(“maternity/e1.png”);
e2 = loadImage(“maternity/e2.png”);
e3 = loadImage(“maternity/e3.png”);
e4 = loadImage(“maternity/e4.png”);
whiteemp = loadImage(“maternity/whiteemp.png”);
blackemp = loadImage(“maternity/blackemp.png”);
hispanicemp = loadImage(“maternity/hispanicemp.png”);
multipleemp = loadImage(“maternity/mixeddemp.png”);
whitegraduate = loadImage(“maternity/whitegraduate.png”);
blackgraduate = loadImage(“maternity/blackgraduate.png”);
multiplegraduate = loadImage(“maternity/mixedgraduate.png”);
hispanicgraduate = loadImage(“maternity/hispanicgraduate.png”);
//slider1 = createSlider(0,100,0,1);
//slider1.position(10,height-70);
//slider1.size(width-20,20);
//x = slider1.value();
console.log(dataRace.getNum(3, “Took Maternity Leave”));
//console.log(dataEducation.getNum(3, “Percent of Women”));

}

function draw() {
background(255);

let whiteNum =dataRace.getNum(1, “Took Maternity Leave”);
let blackNum =dataRace.getNum(2, “Took Maternity Leave”);
let multipleNum =dataRace.getNum(3, “Took Maternity Leave”);
let hispanicNum =dataRace.getNum(4, “Took Maternity Leave”);
let whiteEMP =dataRace.getNum(1, “Did Not Take Maternity Leave – Not Offered or Allowed by Employer”);
let blackEMP =dataRace.getNum(2, “Did Not Take Maternity Leave – Not Offered or Allowed by Employer”);
let multipleEMP=dataRace.getNum(3, “Did Not Take Maternity Leave – Not Offered or Allowed by Employer”);
let hispanicEMP =dataRace.getNum(4, “Did Not Take Maternity Leave – Not Offered or Allowed by Employer”);
let whiteCol =dataRace.getNum(1, “Enrolled in College”);
let blackCol =dataRace.getNum(2, “Enrolled in College”);
let multipleCol =dataRace.getNum(3, “Enrolled in College”);
let hispanicCol =dataRace.getNum(4, “Enrolled in College”);
let lessHigh =dataRace.getNum(1, “Percent of Women”);
let highSchool =dataRace.getNum(2, “Percent of Women”);
let someCol =dataRace.getNum(3, “Percent of Women”);
let colHigher =dataRace.getNum(4, “Percent of Women”);

let y = 25;
let x = 5;
//if(slider1.value() < hispanicNum){
strokeWeight(30);
stroke(145, 86, 34);
line(x+30,y+80,x+30,y+80+hispanicNum);
image(hispanic,x,y,50,85);
//}
//if(slider1.value() < blackNum){
strokeWeight(30);
stroke(51, 30, 12);
line(x+80,y+80,x+80,y+80+blackNum);
image(black,x+50,y,50,85);
//}
//if(slider1.value() < whiteNum){
strokeWeight(30);
stroke(249, 222, 199);
line(x+130,y+80,x+130,y+80+whiteNum);
image(white,x+100,y,50,85);
//}
//if (slider1.value() < multipleNum){
strokeWeight(30);
stroke(183, 143, 110);
line(x+180,y+80,x+180,y+80+multipleNum);
image(mixed,x+150,y,50,85);
//}
//noStroke();
//textSize(30);
//text(slider1.value(),90,200);
//textSize(20);
//text(“% of women”,46,220);
//let edu1 =dataEducation.getNum(
strokeWeight(30);
stroke(100);
line(x+250,y+60,x+250,y+80+lessHigh);
image(e1,x+230,y,45,58);
strokeWeight(30);
stroke(75);
line(x+300,y+60,x+300,y+80+highSchool);
image(e2,x+280,y,45,58);
strokeWeight(30);
stroke(50);
line(x+350,y+60,x+350,y+80+someCol);
image(e3,x+330,y,45,58);
strokeWeight(30);
stroke(0);
line(x+400,y+60,x+400,y+80+colHigher);
image(e4,x+380,y,47,60);

strokeWeight(30);
stroke(145, 86, 34);
line(x+30,y+250,x+30,y+250+hispanicEMP*8);
image(hispanicemp,x,y+200,50,72);
strokeWeight(30);
stroke(33, 20, 9);
line(x+80,y+250,x+80,y+250+blackEMP*8);
image(blackemp,x+50,y+200,50,72);
strokeWeight(30);
stroke(249, 222, 199);
line(x+130,y+250,x+130,y+250+whiteEMP*8);
image(whiteemp,x+100,y+200,50,72);
strokeWeight(30);
stroke(183, 143, 110);
line(x+180,y+250,x+180,y+250+multipleEMP*8);
image(multipleemp,x+150,y+200,50,72);

strokeWeight(30);
stroke(145, 86, 34);
line(x+250,y+260,x+250,y+250+hispanicCol);
image(hispanicgraduate,x+230,y+200,45,58);
strokeWeight(30);
stroke(33, 20, 9);
line(x+300,y+260,x+300,y+260+blackCol);
image(blackgraduate,x+280,y+200,45,58);
strokeWeight(30);
stroke(249, 222, 199);
line(x+350,y+260,x+350,y+260+whiteCol);
image(whitegraduate,x+330,y+200,45,58);
strokeWeight(30);
stroke(183, 143, 110);
line(x+400,y+260,x+400,y+260+multipleCol);
image(multiplegraduate,x+380,y+200,45,58);

}

https://alpha.editor.p5js.org/amena91/sketches/BJpwh9TAb

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