Effective Thesis is looking for funding. I believe the downside risk is very small and we could likely find a way to ensure U.S. tax deductibility. Since this is small meta project, it's not that easy to find institutional support and individual donations might thus have quite large impact on continuation of this project.
Thanks, David! My intuition a bit different - most people I talked to about how got they got into EA mentioned multiple factors, so I was curious whether there would be general patterns/strong clusters of e.g. "offline EA (e.g. local groups + personal contact)" vs "Online EA" or clusters based on type of activity/contribution, e.g. "donation cluster (Givewell + GWWC + TLYCS + ACE)" vs "direct work cluster (80K + EA global)" vs "producing/reading research (books/articles + SSC + LW)". I see it doesn't seem to be the case for the whole sample base don your analysis.
Regarding the more engaged subgroup - while I perceive analysing of "where people first heard about EA" as interesting, the question of "which factors actually got people into EA" seems to me as more important. The more that most people I talked to mentioned that first point of contact with EA didn't cause them to "get into it" right away, but only after encountering some other factors they finally made a step to "dive into it" or "get involved". Therefore, looking whether there are some patterns of these factors for more vs less involved people seems to me potentially promising, I agree that "how long people have been in EA" will probably add a lot of noise to this as these patterns could have changed over time. Not sure whether the sample size would be big enough to analyse each year separately or whether there are some other ways to control for it.
Using cluster analysis for the group membership seems to me like a good example of such approach.
have you tried cluster analysis on the question "Which factors were important in ‘getting you into’ effective altruism, or altering your actions in its direction?"? Since it is multi-select, if most people actually selected more options, information about whether there are some patterns/clusters of factors that are important for people to feel they "got into" EA seems to me like it might be more informative than simple ranking of each factor's frequencies independently.
This might be valuable to try for both, the whole sample as well as specifically for more engaged subgroups as Ben suggested.
Thanks for clarification! I think I have promoted it that way in the early stages, but I have deprioritised the direct impact that theses may create in the past year. The reason is that the value of long-term goals like influencing someone's (research) career focus or building skills/learning more about the issue in order to become better able to work on it afterwards seems much higher than direct impact produced by theses. Also, many organisations don't seem ready to take this kind of help from students and the process of soliciting the results from students is pretty long (students work on their theses from 3 months to 2 years, usually about 7 months) which makes usefulness of such help a bit lower. However, I plan to keep track of the direct impact of theses as well and will update this assumption based on the data I receive.
What do you specifically? The Effective Thesis is focused on helping students with their final thesis projects, there were just a few cases when we helped students with their module thesis or something smaller than capstone project, but I usually deprioritise these cases in favour of final capstone projects.
I'd have thought that nearly all the students would mostly benefit from "general advice on research direction", since specialized EA knowledge is something Effective Thesis has that professors and career offices don't.
That would be my guess as well. Maybe the average advice they would get would not be that good or they would get as good advice anyway from professors and career offices but they got it first from the Effective Thesis and therefore attributed the value to Effective Thesis. However, when trying to estimate the overall counterfactual impact, I have usually rated cases which referred "career advice" or "help with topic they came up with themselves" as the main sources of value they got from Effective Thesis as being less impacted by Effective Thesis than cases which appreciated and used "general advice on research direction".
1. Can you give an example of what "guidance in the topic they came up with themselves" might look like? Particularly in a case where the coach isn't an expert on the topic?
Usually I've tried to match student with a coach who would be expert on the broader domain of the topic student came up with. Example could be a philosophy student who came up with 3 different topic ideas related to global priorities research. The coaching helped him prioritise between these 3 topics and choose the one which would be best in student's situation. Another student came up with a broader topic and coaching helped him take a perspective of the topic, use a specific methodology and/or focus on a specific issue within the topic.
2. Do you have any general observations of where your applications came from? I'd be interested in both the country/regional breakdown and a breakdown of applicant school rankings (e.g. "1/3 from schools in or around the top 100 of this list, most of the rest from other private American/European schools, a few from other continents").
I've asked people "Where did you learn about the Effective Thesis from" in the application form but the results show no specific trend and there are too few cases to draw conclusions from. 5 most frequent channels were word of mouth (14 people), university referral (12), non EA online blog post - Thesis Whisperer (11), facebook referral (11), personal connections/individual outreach (10) and all produced candidates of similar qualities in terms of chance of getting through the funnel, desire to continue in research career and involvement in EA.
I haven't done breakdown by country and school rankings systematically yet, but I will take a closer look and update the post soon. My impression was that people are applying from many countries around the world, even those where there is not visibly large or active EA group and I haven't noticed any strong trend (e.g. that half of the people would be from the UK or something like that). Regarding school rankings, prevalence of candidates from top rated schools is much higher than chance which is in my opinion the result of sampling people from the EA community, however, I need to crunch the numbers to get a more specific information.
Most students haven't finished their projects yet, but I will make another post about long-term changes in students and the impact of their theses after I make impact interview with those who are finishing their theses now (so the post will come out probably during the summer). What specifically do you mean by "being used"? Is it being published in a journal, having reference from some current researchers that it helped them in some way / showed them something new or something else?
Thanks!
Thanks!
Effective Thesis is looking for funding. I believe the downside risk is very small and we could likely find a way to ensure U.S. tax deductibility. Since this is small meta project, it's not that easy to find institutional support and individual donations might thus have quite large impact on continuation of this project.
Thanks, David! My intuition a bit different - most people I talked to about how got they got into EA mentioned multiple factors, so I was curious whether there would be general patterns/strong clusters of e.g. "offline EA (e.g. local groups + personal contact)" vs "Online EA" or clusters based on type of activity/contribution, e.g. "donation cluster (Givewell + GWWC + TLYCS + ACE)" vs "direct work cluster (80K + EA global)" vs "producing/reading research (books/articles + SSC + LW)". I see it doesn't seem to be the case for the whole sample base don your analysis.
Regarding the more engaged subgroup - while I perceive analysing of "where people first heard about EA" as interesting, the question of "which factors actually got people into EA" seems to me as more important. The more that most people I talked to mentioned that first point of contact with EA didn't cause them to "get into it" right away, but only after encountering some other factors they finally made a step to "dive into it" or "get involved". Therefore, looking whether there are some patterns of these factors for more vs less involved people seems to me potentially promising, I agree that "how long people have been in EA" will probably add a lot of noise to this as these patterns could have changed over time. Not sure whether the sample size would be big enough to analyse each year separately or whether there are some other ways to control for it.
Using cluster analysis for the group membership seems to me like a good example of such approach.
Hi David,
have you tried cluster analysis on the question "Which factors were important in ‘getting you into’ effective altruism, or altering your actions in its direction?"? Since it is multi-select, if most people actually selected more options, information about whether there are some patterns/clusters of factors that are important for people to feel they "got into" EA seems to me like it might be more informative than simple ranking of each factor's frequencies independently.
This might be valuable to try for both, the whole sample as well as specifically for more engaged subgroups as Ben suggested.
The update is on, in the section Promotion of the project.
Thanks for clarification! I think I have promoted it that way in the early stages, but I have deprioritised the direct impact that theses may create in the past year. The reason is that the value of long-term goals like influencing someone's (research) career focus or building skills/learning more about the issue in order to become better able to work on it afterwards seems much higher than direct impact produced by theses. Also, many organisations don't seem ready to take this kind of help from students and the process of soliciting the results from students is pretty long (students work on their theses from 3 months to 2 years, usually about 7 months) which makes usefulness of such help a bit lower. However, I plan to keep track of the direct impact of theses as well and will update this assumption based on the data I receive.
What do you specifically? The Effective Thesis is focused on helping students with their final thesis projects, there were just a few cases when we helped students with their module thesis or something smaller than capstone project, but I usually deprioritise these cases in favour of final capstone projects.
That would be my guess as well. Maybe the average advice they would get would not be that good or they would get as good advice anyway from professors and career offices but they got it first from the Effective Thesis and therefore attributed the value to Effective Thesis. However, when trying to estimate the overall counterfactual impact, I have usually rated cases which referred "career advice" or "help with topic they came up with themselves" as the main sources of value they got from Effective Thesis as being less impacted by Effective Thesis than cases which appreciated and used "general advice on research direction".
Usually I've tried to match student with a coach who would be expert on the broader domain of the topic student came up with. Example could be a philosophy student who came up with 3 different topic ideas related to global priorities research. The coaching helped him prioritise between these 3 topics and choose the one which would be best in student's situation. Another student came up with a broader topic and coaching helped him take a perspective of the topic, use a specific methodology and/or focus on a specific issue within the topic.
I've asked people "Where did you learn about the Effective Thesis from" in the application form but the results show no specific trend and there are too few cases to draw conclusions from. 5 most frequent channels were word of mouth (14 people), university referral (12), non EA online blog post - Thesis Whisperer (11), facebook referral (11), personal connections/individual outreach (10) and all produced candidates of similar qualities in terms of chance of getting through the funnel, desire to continue in research career and involvement in EA.
I haven't done breakdown by country and school rankings systematically yet, but I will take a closer look and update the post soon. My impression was that people are applying from many countries around the world, even those where there is not visibly large or active EA group and I haven't noticed any strong trend (e.g. that half of the people would be from the UK or something like that). Regarding school rankings, prevalence of candidates from top rated schools is much higher than chance which is in my opinion the result of sampling people from the EA community, however, I need to crunch the numbers to get a more specific information.
Thanks for the comment!
Most students haven't finished their projects yet, but I will make another post about long-term changes in students and the impact of their theses after I make impact interview with those who are finishing their theses now (so the post will come out probably during the summer). What specifically do you mean by "being used"? Is it being published in a journal, having reference from some current researchers that it helped them in some way / showed them something new or something else?