My (working) Model of EA Attrition: A University CB Perspective

By Juliana Eberschlag @ 2024-05-03T09:29 (+40)

My (working) Model of EA Attrition: A University CB Perspective

Background/Why I’m writing this post:

I've been co-organizing an EA student group at Queen's University in Canada for about a year now. When I first joined Queen's Effective Altruism (QEA) on campus as a general member in January of 2023, the club was small (only ~5 active members and the only HEA was the sole organizer). The following semester, when my fellow co-organizer and I inherited the club, we were pleasantly surprised with the number of members joining QEA—we attracted 40 members over the semester, with an active member base of ~17. Everyone seemed pretty interested and engaged, and we managed to send a total of 8 members to various GCPs and EAGs. We noticed some attrition, but not enough to pass it off as anything more than what was expected (in fact, our club collected more members than we lost over the semester.

Then winter semester rolled around. All of the sudden, our active member base fell to ~10, albeit we absorbed some of the previous EA members into exec roles. Our attrition rates were also notably higher: By the end of the semester, some of our introductory fellowship meetings, which initially attracted around 17 attendees, dwindled to just one or two participants.

This difference seemed significant. Of course, there are many expected variables (winter semesters tend to involve higher attrition rates, the recruiting period is less bustling than the fall recruiting period, etc.). But, with the knowledge of the success we had in the fall, the contrast was stark and rather confusing, especially since we put in the same—if not more—effort into the club during the winter semester. Some of the members who we thought would stick, didn't, leading to even more confusion.

I've grown increasingly interested in attrition—namely, questions related to what qualities the people who reject/tend towards EA ideas possess, what factors contribute to attrition, and how to discern whether it reflects issues within our university club or is just noise.

As I've thought about this more, I've come to discern some patterns in attrition, which, I think, hint at the potential for a comprehensive model. Developing mental models has been incredibly helpful for me. When I notice confusion about something with no clear way out—no model to grip onto and make sense of the thing—I succumb to inertia. The same can be said about this model of attrition: The more I cultivated a model, a mental heuristic to employ when considering membership for QEA, the more clarity I've had about thinking about membership, and thus the more confident I felt about taking action according to it. This post aims to go over some of these trends/little things I've noticed that I think are helpful to be aware of as a university community builder.

Note: I've been uncertain about the usefulness of this discussion. Much of what I've noticed might seem self-evident, but maybe this is due to the illusion of transparency or the curse of knowledge fallacy. Regardless, I've concluded that I think there is at least no harm in posting this. At its best, I think this post could open up further discussion about attrition in EA broadly—not as a means of reducing it, as attrition is healthy and normal, but as a means of having a better prediction model.

It's also important to clarify that this model isn't meant for preemptively judging potential members. Instead, it aims to provide community builders with strategic insights—identifying where to intensify or ease recruitment efforts based on understanding likely member engagement. This approach isn't about convincing everyone of EA; rather, it's about efficiently selecting and connecting with individuals who are naturally inclined toward the principles of EA. Gaining even a basic understanding of who these individuals might be can better our focus and effectiveness as club leaders, ensuring our energies are well-positioned for optimizing our CB efforts.

My (very rough) model of what repels/attracts university students to/from EA:

*This is mostly based on conversations with QEA members of varying commitment levels—so all anecdotal, qualitative observations, with a small sample size.

Of course, there are overarching factors that largely do not lay in the control of community builders:

The factors I'm more interested in are those that come down to individual factors, like personality, interests, dispositions, etc. Here are some other factors and/or general considerations:

Other things worth saying:

Please reach out if you have any thoughts on this :)


Nathan Young @ 2024-05-03T12:39 (+7)

Solid piece. I like lists of things and I appreciate you taking the time to write one.

I sometimes wonder how to combine many qualitative impressions like this into a more robust picture. Some thoughts:

Abhay Katoch @ 2024-05-04T15:34 (+1)

Hi Nathan, I'm one of the co-organizers along with Juliana and I've thought a lot about quantitatively measuring attrition rates and the types of people more interested in EA. 

We found it hard—at least on the level of one club—to measure things like attrition rate for a few different reasons:

  • First, there are so many factors that may cause someone to attrit from a club, ranging from them not being a good fit to them simply not having the time (as @DavidNash mentioned). 
    • These factors also are so variable: as Juliana mentioned, if she didn't like interacting with her group (me especially) as much, she probably wouldn't have continued engaging in EA. One bad session or rude person in your group may make the difference between a person continuing to engage or leaving. 
    • These factors all also have such small effect sizes and also intersect with each other, to the point that it becomes very hard to suss out any sort of causality or clear picture from quantitative data. 
      • This is where (in my experience) these more qualitative approaches become more useful, as we are naturally attuned to gathering peoples' impressions. 
  • Second, there's going to be a lot of selection bias: most people (at least I would suspect) in most universities aren't interested in EA (again, for many factors) and so any confusion matrix of people 'interested/not-interested in EA' and 'whether they join' is going to be very heavily weighted towards 'not-interested x not join'. And so the vast majority of people who come to an information night or express some sort of interest are not leaving for any particular reason, but rather because they just aren't interested in EA [enough].

 

But as you mentioned, there may be a lot of value in sort-of qualitatively-quantitatively measuring attrition rates on the scale of CEA—instead of trying to find reasons as for why people are not staying on a group-level, the CEA Groups team could survey reasons for why group organizers think people leave, and perhaps use that to create helpful resources.

DavidNash @ 2024-05-03T10:40 (+6)

One category that you didn't include are people that agree with the ideas and take action, but don't want to or are too busy to attend lots of EA meetups.

Abhay Katoch @ 2024-05-04T15:46 (+1)

Hi David, I think that is actually quite a big factor! I noticed in particular that there are people in our group we think are particularly well-suited for EA but don't have the time and/or energy to engage. These sorts of people agree with the ideas, are motivated to make an impact, and also have sufficient work ethic to do so, but can't make it to the meetings precisely because they're too busy making an impact. I personally think these people are the ones we want to expose to EA ideas, but it is difficult to engage them.

We have a couple different ideas for engaging these sorts of people more: 

  • First, having a strong community and friend-group associated with our group creates a social obligation (for lack of a better word) to attend, and also makes it more fun to attend. The people in this community will also have lots of EA-adjacent people in their network and/or other friend-groups, who would also be exposed to EA ideas. 
  • Second, having low-commitment events at non-busy times of the year (e.g., a social event early in the semester) means that those sorts of people are more likely to attend. This also introduces them to the 'community' I mentioned earlier, which allows them to be more engaged.
  • Third, as you mentioned, we also find a lot of value in having a more 'wide' network of EA-affiliated people on our campus, rather than just having a tight-knit community and encouraging people to join. Not everyone is looking for an EA-style community, but may still want to engage with the ideas, or want career advice (we've noticed a few people like that). This also allows people to move in and out of the wider 'network' and tight-knit group with ease, (hopefully) reducing attrition. 
SummaryBot @ 2024-05-06T14:02 (+1)

Executive summary: The author presents a working model of factors that attract or repel university students from Effective Altruism (EA) based on their experience as a co-organizer of an EA student group, aiming to provide insights for community builders to optimize their efforts.

Key points:

  1. The author noticed significant attrition in their EA student group membership, prompting them to develop a mental model to understand the factors contributing to this trend.
  2. Overarching factors like economic incentives and self-interest play a role in attrition, but the author is more interested in individual factors like personality, interests, and dispositions.
  3. Lack of intrinsic intellectual interest, convenience/cherry-picking of EA ideas, being more impressionable/less independent, and different thresholds of obligation are some key factors that may repel students from EA.
  4. The degree to which someone is naturally "rational" and their preconceived notions of altruism can also impact their engagement with EA ideas.
  5. The author emphasizes the importance of understanding, humility, and avoiding blame when considering EA attrition, acknowledging the complexity of factors involved in continued participation.
  6. School culture and self-selection effects may also influence the likelihood of students being drawn to or repelled from EA.

 

 

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