It seems like your approach would suffer a lot of selection bias and would need to collect a lot of data before it would be useful, hence it'll be hard to bootstrap contributors.
I'm not an academic, but wouldn't a better strategy be to do co-authorship analysis on papers to generate similar information. That is you could say researchers who co-wrote their initial papers with more senior researcher X (normally indicating a supervisor or mentor relationship) at lab Y tend to end up at Z and have an average research impact score of R.
That way you could get all the data from analyzing public citation databases and avoid the chicken-and-egg problem with trying to crowdsource the data, and go directly to solving the main problem of comparing potential PhD supervisors based on their trackrecord.
Love that idea. That could also lead to an interesting analysis which institution the co-authors give as their home institution. Might be even demonstrate causality, e.g. researcher X from institution X works with researcher Y from institution Y and later researcher X joins institution Y as well. I'm suspecting there are some academic tribes out there.
Comments
It seems like your approach would suffer a lot of selection bias and would need to collect a lot of data before it would be useful, hence it'll be hard to bootstrap contributors.
I'm not an academic, but wouldn't a better strategy be to do co-authorship analysis on papers to generate similar information. That is you could say researchers who co-wrote their initial papers with more senior researcher X (normally indicating a supervisor or mentor relationship) at lab Y tend to end up at Z and have an average research impact score of R.
That way you could get all the data from analyzing public citation databases and avoid the chicken-and-egg problem with trying to crowdsource the data, and go directly to solving the main problem of comparing potential PhD supervisors based on their trackrecord.
Love that idea. That could also lead to an interesting analysis which institution the co-authors give as their home institution. Might be even demonstrate causality, e.g. researcher X from institution X works with researcher Y from institution Y and later researcher X joins institution Y as well. I'm suspecting there are some academic tribes out there.
Yes, that's definitely one interesting direction we should go pursue. Thanks a lot!