You searched for all stories that contained the words listed under "selected filters" below. This retrieved 300 stories.
How to interpret the icons: Note that the phrase "women group" makes this collection of stories
even more positive than stories about women and group. This positive trend has
more to do with the likely fact that all these stories are from people talking about
a group they belong to, and they only want to focus on the benefits, not the problems.
Over half of these stories are from people affected or directly involved, as seen if you
click on the pie charts button below.
Trends (Benchmarked against all stories we've ever collected)
Responses (within this story collection, not benchmarked)
Q37|Good idea that succeeded Q37|Good idea that failed Q37|Bad idea Q37|mixed Q37|Good idea that worked somewhat Q37|Good idea that should have worked but did not
Q38|Mixed Q38|Specific problem Q38|Broad need Q38|Specific solution
TOP ANSWERS:The right people,Inspired,Good idea that succeeded: 2705 --- The right people,Happy,Good idea that succeeded: 2084 --- The right people,Important,Good idea that succeeded: 1537 --- The right people,Hopeful,Good idea that succeeded: 1336 --- The right people,Hopeful,Good idea that worked somewhat: 223 --- The wrong people,Important,Good idea that succeeded: 206  Benchmark processing time:0.51s
(Narratives and answers to any associated survey questions)
Why use benchmarks?
By now you probably noticed that the size and color of icons are pre-adjusted or "benchmarked" against a reference data
point. By default the reference is "all other data we've ever collected" but you can customize that benchmark to be something specific and logical to your question.
Benchmarks are important! This is what raw data from a typical collection would look like without benchmarking:
First, everything is green. People are 10 to 20 times more likely to be positive in stories than negative, depending on how they were prompted.
Second, the results now emphasize the unevenness of the sample across age and gender. Like the positive story bias,
this uneven sample is nearly always present in data. Instead of throwing out all of the data, we display results
weighted against a large reference sample, so that any collection of randomly selected stories will look like this:
Every icon is yellow (neutral) and medium-sized, because they are a representative sample. If you asked 100 people to participate,
this would be the breakdown of who responds, based on asking over 60,000 people so far.
But if you wanted the benchmark to be 100% women, you can select that with "compare" tool, explained later.
Using quotes to search for phrases
You searched for "women group".
Notice that putting quotes around two words narrows the number of stories that appear in your collection.
However, a more powerful and flexible way to search for stories is you put a bunch of words inside parentheses,
like ("women group" "womens group" "self help" woman and group) instead of None.
The search engine will include stories that have any one of these words inside the parentheses.
Try searching for
("women group" "womens group" "self help" woman and group)