Accessing Holistic Review Scores

What is holistic review?

A holistic review approach identifies individuals whose unique strengths align with a program's goals by considering multiple dimensions – such as personal attributes, experiences, skills, and academic performance – rather than focusing disproportionately on just one or a few factors like test scores.

What is the holistic score?

To assist in the holistic review process, WebAdMIT automatically calculates a holistic score for each applicant. This scoring model was developed by Othot, Liaison's data science team, which has over a decade of experience in the field. The model is:

• Research-based: developed through rigorous research, incorporating feedback from both the community and experts.
• Explainable: unlike some data science models that function as "black boxes," where it's challenging to interpret how they arrive at their decisions, this model's algorithm is designed to be comprehensible.
• Customizable: flexible and can be tailored to align with your program's mission, goals, and values.

How can I use the score?

You can choose to use the holistic score at your discretion. For example, you may choose to use the List Manager to find and sort applicants by score and prioritize reviewing those with higher scores. Additionally, you may find that the holistic nature of the tool brings to your attention applications that align with your mission, goals, and values, and might have otherwise gone unnoticed.

When using the score, note the following:

• This is a "surfacing tool."
  • Programs may find this tool useful in identifying an initial set of applications that should be prioritized for review.
  • Alternatively, you might choose to use the List Manager to find specific subpopulations of the applicant pool and then review the holistic score.
• You can customize how the scoring components are weighted so they align with your program's values.
  • The weights represent the relative priorities of different elements of the application to your program and how applicants compare to other applicants within your cohort.
  • Note that while you can adjust overall weightings, you cannot add or create custom scoring elements, adjust the weights for individual applicants, or adjust any final calculated scores.
• This is not meant to be used as a precision instrument.
  • You should look at the score in relation to the other scores; the absolute score is less relevant.
  • For example, an 88.1 score is not meant to be far better than an 87.9 score.
• This is not meant to replace reviews.
  • If you currently use Assignments or other reviewing tools with your review team, you should continue to do so.
• This model will continue to evolve as we collect program feedback.

What are the key scoring concepts?

• The scoring model uses direct data to calculate scores.
  • The model does not attempt to infer things, such as by counting words in a personal statement or using other less reliable data analysis methods.
  • Scores are derived from real data elements provided in the application or in official supplementary materials, such as MCAT scores.
• Each data element is calculated as a percentile score relative to other applicants to the program.
  • All data element scores are scaled from 0 to 100 (including binary variables).
• The scoring model organizes application data elements into domains and subdomains.
  • Domains are overarching categories, while subdomains provide further granularity within a domain.
• All scores and percentiles in the model are calculated within your program's cohort of applicants, not against the general applicant pool.
  • As a result, each applicant receives a unique score for each program, reflecting their comparison to other applicants within the same program.

How are scores derived?

When you click a score, a breakdown appears in a four-column table.

1. On the left are the domains (categories of data elements), some of which can be expanded to show subdomains (such as Undergrad Background).
2. The Original Score column lists a set of scores assigned to the applicant, ranging from 0 to 100. These scores are derived using a percentile calculation method.
   • For each data element included in a domain and subdomain, WebAdMIT assesses how each applicant's performance compares to that of others applying to the same program. Once these percentiles are determined, they undergo a rescaling process, converting them from percentile values to a standardized 0 to 100 scale. This ensures a fair and consistent evaluation of applicants' standings within the applicant pool.
   • If a data element is missing, how it's handled depends on its importance. Missing values for critical elements are treated as zero. For non-critical elements, the weight is redistributed across the remaining domains and subdomains to avoid unfair penalization.
3. The Weight column displays the weightings assigned to each domain and subdomain, which you can customize.
4. The Weighted Score column displays the weighted score for each domain and subdomain, which is the multiplication of the original score by its weight.

To calculate the Total Weighted Score, the weighted scores for all domains are summed together.

Editing Holistic Review Weights

Click Edit to update domain and subdomain weights.

Removing Your Manually Distributed Holistic Review Weights

Click Edit, then click the red x next to a manually distributed weight. The applicable domain and/or subdomain percentages will automatically readjust to be evenly distributed.