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She went on to say that mainstream data focus is still in what she calls the “malestream” perspective. This perspective of data collection, she said, is very focused on certain aspects of women’s data.
Seager explained that finding data on women who are paid in the workforce is pretty simple to obtain. This is an example of productionist data. But finding women’s data in reproductionist data can be difficult to do.
Examples of reproductionist data for women that are easy to find includes the number of children women have, maternal mortality and contraceptive use. But what’s missing is abortion laws and standardized compilation of women’s reproductive autonomy, Seager said.
Seager’s next topic in her presentation was entitled “missing bodies.” This is where she brought up the fact that entire categories of women are missing.
According to Seager, this is caused by two different problems.
“[There is] very little curiosity about women’s lives,” Seager said. “[And there is] very little disaggregation rendering both men and women in separate agencies.”
Seager believes that the way to fix this would be to start collecting gender-disaggregated data. She explained that gender-disaggregated data could be used to inform policy.
“For policymakers, a gender analysis provides a sounder basis to make decisions,” said Seager.
The next point she brought up was the collection of “household data.” Getting this data gives off the impression that they are gathering more informed and accurate data, but it is actually undermining women in most cases.
The use of household data is seen as a standard measurement for data collectors. But in most households, the man is the head of the house, so he would answer for the household even though the other people living in the house could have differing opinions. Seager believes that this method of data collecting creates a gender empowerment gap and gives, at best, a partial view.
“[This] makes women particularly invisible because of gender dynamics,” Seager said.
Around the world, the most available gender-disaggregated data are mortality rate, which is at 85 percent. But the least gender-disaggregated data are media at 15 percent. As Seager said earlier in her speech, gender disaggregation can help people make more informed decisions. So she believes that the way to get there is to start collecting the data.
But in the meantime, Seager gave the audience some advice on what they should do for the time being.
She said that people should always advocate for disaggregation and that consumers should always be alert to this, making them “critical consumers.” In a separate interview after her presentation, Seager elaborated on the idea of becoming a “critical consumer,” saying that consumers have to “start to become aware.”
“Measurements count, because if it’s not counted, it’s assumed to be unimportant,” Seager said. The lack of representation of women in data has done just that. But if more women’s data تحليل فوركس للذهب is collected, women will be seen as important.
Audience member Lawrence Palagi, a former geography teacher who is currently a National Geographic teaching consultant, initially thought that the presentation could isolate men. Instead, he found it was geared toward both men and women.
“I thought it was very inclusive,” Palagi said.
Palagi went on to say that he agrees with Seager in that data collectors should be getting more gender disaggregated data.
“I can see her point about getting statistics,” he said.
Audience member and curator of maps in the Norman B. Leventhal Map Center at the Boston Public Library Ronald Grim had a little more sympathy for data collectors.
“I think we often look at maps and think it’s easy to find data,” Grim said. “Trying to find consistent data on a global scale is really difficult.”
Seager believes that regardless of the reason why there is a shortage of women representation in both data and maps, that is no reason to accept it.
Seager finished her speech with a directive.
“Resist the complacency of the apparent data surfeit,” Seager said.
Photo courtesy dirkcuys, Creative Commons