u/Spiritual_Piccolo793

We have sanskari players while MI has chapri players.

Look at Jaisu - such a handsome heartthrob and yet doesn’t have a gf. Hardworking boy, who never abuses anyone and always does what is asked of him. Doesn’t fight and gives away his ODI and T20 positions like an obedient kid.

Vaibhav - never boasts about himself and does charansparsh of everyone elder to him.

Parag - dances on Assamese song, searches online for girl pics like a hardworking middle class boy, and tries extra hard (overdo) in his captaincy when not needed.

Jurel - fan of Rahul Dravid, who we all know is OG sanskari

Archer - works as hard as bihari labourer on field, never shouts at missed catches, and no 3 extra gfs like other WI players

….
Now let’s look at Mumbai: everyone has either a tattoo or vada pav in their hand. More specifically:

Pandya - OG chapri. Goes into another person’s wedding and arranges his own honeymoon.

Tilak - Nanga ladka.

Surya - No responsibility for matches and his own health. We all know how papa used to scold us that eating chewing gums all the time damages your teeth and health.

…

https://drive.google.com/file/d/1j97BpC7Jc9-h7H6Y1wmSmLjeW9C9d3GL/view?usp=sharing

Thank you all for your input, without which creating rankings would have been impossible.

When I started the exercise, I had thought that devising the rankings would take me a maximum of two weeks. However, weeks passed and I ended up investing close to 3 months. Hopefully, next year it will be an easier exercise.

The rankings methodology changed significantly over the months. Initially, I had been assigning a fixed score or a rank-based penalty to postdocs, which would underestimate the schools with a higher postdoc %. Overall, I realized that the next-career move for postdocs needs to be considered. As I began to investigate the data, realized that a significant portion of the postdocs do not transition out of the role. Hence, it became imperative to correctly assign a score to those cases. There is an inherent bias in terms of recent cohorts having a higher share of non-transitioned cases. This implies that one needs to add a penalty to the final resolved placement for a given postdoc; where the penalty is dependent on the time they had spent as a postdoc.

But how to assign a score to the cases, where we don't have a next career move? For those cases, used a CatBoost model to estimate the expected scores using the transitioned postdoc data. All of these have been explained in detail in the methodology section.

Even though the modeling approach is a step in the right direction, there is scope for improvement. For instance, placement data is inherently biased (due to biased reporting); hence, one needs to tackle such cases. Currently, we use fixed-tier rankings for placements at Central Banks and International Organizations. Maybe more sophisticated approaches can be brought into the picture.

Initially, I would consider placements in think tanks and government agencies via a fixed tiered scoring method. However, I realized that government placements can be all over the place and not necessarily in research roles. Initially, I did try to segregate the research ones and assign a fixed-tier score. With the government fixed-tier score, the rankings seemed off.

Eventually, I had to drop rankings for international schools. I had spent a considerable amount of time to come up with an objective ranking. Unfortunately, even after 3 months, I could come up with no method that would objectively place Erasmus Rotterdam over the University of Amsterdam. I have no preference for any school, but quite a number of folks suggested that Erasmus is a better school compared to other schools among the Dutch programs.

Given that all the objective strategies fail to place Erasmus over other Dutch schools, I think there is something systematic that might be happening. I have looked at data countless times and yet the issue persisted.

I am more than happy to share the data for free (under a data sharing agreement) in case anyone wants to do research using them.

As PandaInUniv grows, you will continue to see richer and richer data. The data quality and standardization have improved significantly over the last 6 months. We will soon start reporting advisor names against doctoral students, suggesting an average advising quality based on placements.

The goal of PandaInUniv is to bring transparency to academia. For many reasons, there is an inherent opacity in academia, and our goal is to reduce that as much as possible. We also want to voice student concerns: in case you think you were discriminated against or harmed by university policies, please do reach out to us. We will give you a platform to raise your concerns (anonymously, if you prefer). For industry, we have glassdoor. Where is the equivalent of that in academia?

I plan to send the rankings to school admins on Monday. Hopefully, they get forwarded to you. I do hope you guys continue to support the endeavor. I can't emphasize enough how much your support means to me.

Next match is a must win. Ideally we should win but let’s not leave things to chances. MI is going through an internal turmoil. Let’s take advantage of it.

Let’s pretend to be a fan of Surya, Tilak, or Rohit and abuse Pandya on his Instagram page for being a chapri. Viceversa, pretend to be a chapri and abuse Rohit for liking Vada Pav or Surya for Rosogollas or Tilak for trying to be more black than Pandya. We all should remember than Pandya is the OG black. Also, we need to take revenge for Pandya giving our captain a heartbreak in Ambani’s marriage, which led to a drop in his performance.

This strategy will create more fissures and infighting in the MI camp. That’s all we need. Rest, Boss Baby will handle.

Joking folks, don’t take it seriously.

Good news for us! In case we don’t win all three we can still go to top 2 and certainly top 4.

Mitch Marsh you beauty!

I know might sound like a cliche! But Suryavanshi has just been names in the team against Srilanka! This will energise him! So us the case with Jassu who has been named in the main team.

Could sense that were a bit depressed and disappointed. The news should calm their nerves and energise them.

RR Management ki …

They can give tons of opportunity to Hetmyer and not one to Ravi Singh, Aman Rao, and Milne?

https://preview.redd.it/nv9uzmpjc4zg1.png?width=2282&format=png&auto=webp&s=8d609728b0ab1327ca781a55c62bcac3e659e1cb

https://preview.redd.it/f5ewqk3oc4zg1.png?width=2052&format=png&auto=webp&s=fe646bd72f84b46936ee8bf0c718bbaa15df8b60

How come European programs don't have teaching placements? This is not a data collection issue. Wondering what could be the reason?

Link:https://drive.google.com/file/d/10DZh2FXIEaokYx2Nv8V0jq63lQhySXgM/view?usp=sharing

Back with an update on economics rankings based on placements data available on PandaInUniv ( pandainuniv.com ).

Had received a tons of feedback and suggestions over the previous versions. Previously, I had worked on improving the data quality etc. What changed? Had realized that assigning a constant score to postdocs etc. undermines the programs who place folks in postdocs. Hence, I look at the next career move for postdocs. Tried to devise a mechanism that properly integrates the next career move of postdocs within the rankings system.

Here is the logic that I ended up with: next_career_repec + (terminal score - next_career_repec) * w, where w is the logit score which grows with time. This implies that the longer someone remains as a postdoc, the value assigned to their next tenure-track placement continues to depreciate. This formula incorporates both the information available to us: someone being a postdoc and the transition from being a postdoc to a permanent job. Terminal score is the default fixed value assigned to someone who remains as a postdoc for a longer period of time (we have assumed transition at 3 years; at 5 years w is around 95%). Terminal score is higher than a tenure-track score at a repec ranked or unranked school. Assumption being that a terminal postdoc is a relatively worse placement compared to having a tenure-track job.

As always, I am extremely thankful to this community. PandaInUniv survives due to the constant guidance and support from you folks. Looking forward to the feedback on the updated rankings.

:)