Update: Using the data I compiled for this post, I have created estimates for the percentage of men and women participating in all UACES 2018 panels. That analysis can be found here.
During the 2018 UACES conference on European studies in Bath at the beginning of September, I created several social-network visualizations of panels and participants. The visualizations that focused on participants explored both the number of connections each person had to others, and the 'betweenness centrality' of each person in the network (a measure of their importance for holding the network together).
There are obvious differences between the centrality scores of the nodes: the highest betweenness score is 21,203, while over 70% of nodes have a score of zero (because betweenness centrality is a measure of how often a node is on the 'shortest paths' between nodes).
However, there is almost no average difference based on gender, where scores are almost identical (951.1 female participants, 955.3 male).
Focusing only on the 150 participants with a betweenness centrality score above zero, men were more heavily represented in top-20 highest scores, but this evened out in the top 50 and top 150.
Number of connections
The second way I looked at the issue was through the number of connections participants had with others (weighted degree). The average number of connections overall was 7.4. This average masks a wide range, from a low of 2 connections to a high of 32 connections.
On this metric, male participants had an average about 10% higher than their female colleagues (7.1 female vs. 7.8 male). Male participants also made up a high percentage of the top 20 nodes by weighted degree (although this once again was reduced to 50-50 for the top 150).
Conclusions
A few key findings jump out from this brief analysis.
First, the gender of participants this year was split almost 50-50, in contrast to findings in other disciplines and venues.
Second, there was almost no difference in the average network centrality by gender, and a 10% higher number of connections for male participants.
Third, this broad similarity on average masked a heavy percentage of male participants in the top scores of both centrality and number of connections.
I'd emphasize again that these results should be interpreted with caution: they are preliminary, from one year and one conference, and focus on a single aspect of the dense social networks that exist in these gatherings.
But they do raise interesting further questions:
How have these and other metrics changed over time, in UACES and beyond? What are the differences between areas of focus (e.g. gender studies, environmental policy, foreign policy)? And how do these findings fit into the rich existing academic and societal discussions on gender issues?
I hope this analysis can be an interesting, if small, part of that wider conversation.
During the 2018 UACES conference on European studies in Bath at the beginning of September, I created several social-network visualizations of panels and participants. The visualizations that focused on participants explored both the number of connections each person had to others, and the 'betweenness centrality' of each person in the network (a measure of their importance for holding the network together).
Two academics who attended the conference - Dr Toni Haastrup and Dr Katharine Wright - asked me about the gender dimensions of these topics (for much more expertise on gender in EU studies, a good place to start is the UACES Gendering EU Studies research network).
This took additional analysis because the gender of UACES participants was not given on the conference website. So I coded the gender of each participant and added that data to the network maps (like my earlier maps, all participants were anonymized).
This approach has important limitations: for instance, it is based on my own analysis and not conference participants' self-identified gender. In addition, the results are broad and show only the formal connections between participants, e.g. not those who attended each panel in the audience.
But the results are nevertheless interesting. Below I've focused on two aspects: network centrality and each participant's number of connections.
But the results are nevertheless interesting. Below I've focused on two aspects: network centrality and each participant's number of connections.
Network centrality
After removing duplicates, the UACES program listed 522 participants. The gender split was almost exactly 50-50: 258 people were female (49.4%) and 264 were male (50.6%).
The map below shows network participants color-coded according to gender (green is female, blue is male) with node size determined by betweenness centrality, which the network analysis program Gephi defines as "how often a node appears on shortest paths between nodes in the network".
 |
| UACES 2018 participants weighted by network centrality. Participants are connected when they participated in the same panel. Green nodes are female participants, blue nodes are male participants. Node size is related to a participant's centrality in the network (betweenness centrality). High-resolution, searchable PDF is available here. |
There are obvious differences between the centrality scores of the nodes: the highest betweenness score is 21,203, while over 70% of nodes have a score of zero (because betweenness centrality is a measure of how often a node is on the 'shortest paths' between nodes).
However, there is almost no average difference based on gender, where scores are almost identical (951.1 female participants, 955.3 male).
Focusing only on the 150 participants with a betweenness centrality score above zero, men were more heavily represented in top-20 highest scores, but this evened out in the top 50 and top 150.
 |
| Percentage of female/male participants with the highest betweenness centrality scores. |
Number of connections
The second way I looked at the issue was through the number of connections participants had with others (weighted degree). The average number of connections overall was 7.4. This average masks a wide range, from a low of 2 connections to a high of 32 connections.
 |
| UACES 2018 participants weighted by number of connections (weighted degree). Participants are connected when they participated in the same panel. Green nodes are female participants, blue nodes are male participants. Node size is related to a participant's number of connections (weighted degree). High-resolution, searchable PDF is available here. |
On this metric, male participants had an average about 10% higher than their female colleagues (7.1 female vs. 7.8 male). Male participants also made up a high percentage of the top 20 nodes by weighted degree (although this once again was reduced to 50-50 for the top 150).
 |
| Percentage of female/male participants with the highest weighted degree scores (number of connections). |
Conclusions
A few key findings jump out from this brief analysis.
First, the gender of participants this year was split almost 50-50, in contrast to findings in other disciplines and venues.
Second, there was almost no difference in the average network centrality by gender, and a 10% higher number of connections for male participants.
Third, this broad similarity on average masked a heavy percentage of male participants in the top scores of both centrality and number of connections.
I'd emphasize again that these results should be interpreted with caution: they are preliminary, from one year and one conference, and focus on a single aspect of the dense social networks that exist in these gatherings.
But they do raise interesting further questions:
How have these and other metrics changed over time, in UACES and beyond? What are the differences between areas of focus (e.g. gender studies, environmental policy, foreign policy)? And how do these findings fit into the rich existing academic and societal discussions on gender issues?
I hope this analysis can be an interesting, if small, part of that wider conversation.
