Meta-data Conceptual Relationships

Join us in exploring our on-line case studies and e-Dialogues by investigating where key concepts obtained from the Community Research Connections coding framework intersect. This intersection reveals which ideas and concepts have the strongest connections or relationships, if any.

How do concepts intersect?

Where concepts intersect was determined by using a coding similarity analysis. Concepts with a higher degree of similarity, which is based on the occurrence and frequency of each, are ranked higher on the scale than those that show a lower degree of similarity.

This analysis allowed us to explore how the concepts overlap or relate to each other within the case studies and e-Dialogues text. We believe the higher the degree of overlap, the stronger the connection there is between these concepts, thereby providing a recipe with which to understand which ideas are connected, to further explore possible co-benefits of acting in one area with another, and potential complimentary actions. 

How do you determine concepts are related?

Relationship is measured using the Sørensen coefficient which produces values ranging from 0 to 1, with 0 being least similar and 1 being most similar. To see the results of the analysis, we plotted the concepts (y-axis) according to the strength of the relationship (x-axis). For each concept on the y-axis their corresponding concept is represented with a circle. Larger circles show a stronger degree of similarity. Concepts are arranged in the vertical space according to their prevalence in the case studies and e-Dialogues.

You can search all the data by selecting all or conversely, individual data by using the drop down box. This allows you to compare and contrast specific concepts. The Sørensen coefficient filter located at the bottom of the graph allows you to zoom in and out of the x-axis highlighting concepts that fall within the selected range.

Click here to return to the CRC Meta-analysis page.