RT101: 2015 Ratings. 7/15/2015. Objectives. A few norms for this session. No technology required during this session, though feel free to take notes however you are most comfortable Please feel free to ask questions as they come up
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Familiarity with selection model
Lots of other things…
Approach: fully source a diverse prospect pool and tailor the recruiting approach appropriately
Approach:build a system that objectively categorizes (rates) prospects by their likelihood of admission
Approach:fully source a diverse prospect pool and tailor the recruiting approach appropriately
Approach: build a system that objectively categorizes (rates) prospects by their likelihood of admission
Today is focused on the ratings system to prioritize prospects based on admission
Probability of Admission by Rating
A Brief Note on Probability
Here’s the rating!
Let’s zoom in on the first three data points
You are correct! Trudy holds two moderate leadership positions depending on the selectivity of the Orientation Assistant role (but the RA role almost always indicates moderate leadership). Even though there are two roles, we still only use the most selective one to calculate leadership.
You are exactly right! Neil’s leadership is a minor, less selective role on campus.
Ratings change and become more accurate the more data we have on a prospect
*Important notes: the PRT also uses prospect type and school in its prioritization algorithm. While these are not direct proxies for selection competencies, they are useful information for predicting probability of admission; this is helpful for PRT prioritization because MPRs manage more heterogeneous prospect pools than RMs
You will learn a lot more about the specifics of above in future sessions
Ratings are an automated system on a 1-10 scale that helps prioritize prospects for Outreach/Cultivation by predicting probability of admission
Ratings are a proxy for the selection model because the components used for rating approximate many of our selection competencies