Seems like a paper from a young student who needs to get his 3000 wordcount.
It just bloats the article and makes it difficult to get the information out of it.
I think it's great, it shows there's always a human side to trends and large statistics.
Call me inhumane, but a single story doesn't mean anything. It's just some random point in the set. Drawing any conclusions from such a single point is dangerous (the larger the set, the more), as we humans just love to extrapolate single points and even tend have quite strong emotional defenses about their importance.
To remove the emotional part, just think of something from IT, like response times or test coverages. See, a story of an obscenely long API response (out of thousands) doesn't make much sense anymore. Debugging individual cases may even lead you on a completely wrong track. Unless you want to merely resolve that particular single request.
I'm sorry about the tone. Stories about others make humans relate (which is good), but they also have such undesirable effects (hype over facts, extrapolating, etc).
Averages and generalizations only tell a portion of the story. Anecdotes can shed light on "noise".
This incentivizes increasing employment percentage. An easy way to do that is by decreasing the value of a job. Suddenly it doesn't ensure you can build a living, own a home, support a family anymore. But it is still used as a primary measure of the wellbeing of the economy.
This is why you need individual stories to interrogate the quality of your data. Afterwards, you obviously need to come up with new measures that more accurately reflect how well the economy is working for the people in it. But the interrogation will have to work on the basis of anecdotes.