RNL enrollment and financial aid models

To Whom It May Concern:

Pursuant to the Nevada Public Records Act, I hereby request the following records:

1) All contracts with Ruffalo, Noel, Levitz (RNL) since Jan. 1, 2018 for enrollment management and financial aid optimization services.

2) The following documents/reports provided to the university by RNL since Jan. 1, 2018:

- ForecastPlus model reports for the prospect model, inquiry model, and admit model . I have attached an example of one of these reports from the University of Nebraska-Kearney, for your reference.

- Historical Research & Competitor Benchmarking reports. RNL describes these documents as "a comprehensive investigation of undergraduate student enrollment behaviors related to their needs, academic credentials, population segments, and financial aid offers (approximately 100+ pages)."

- Econometric Modeling reports. RNL describes these models as "logistic regression models based on two or three years of historical information and the goal is to understand ... how student variables, such as household income, ZIP code, academic profile, etc. interact with one another, so we can predict how changes in some variables will affect the future course of others."

- Revenue Optimization & Simulation reports. RNL describes this service thusly: "this tool determines the appropriate amount of financial aid—down to the student level—and creates a series of optimized awarding parameters that can influence the recommended awarding structure."

3) De-identified copies of all enrollment and financial aid model datasets received from RNL for 2021-2022 school year applicants, containing:
- All non-identifiable variables for each applicant that the university supplies to RNL for the purpose of building and training its predictive models (i.e., GPAs, majors, test scores, etc.)
AND
- All output data fields (i.e., model scores, receptivity scores, lead categories, etc.) generated by RNL's predictive models for each applicant.

With regards to item 4 of my request, please note that I am asking for a de-identified data set that does not include fields that could be used to identify an individual applicant (e.g., name, address, SSN). These fields can easily be redacted by deleting those columns from the responsive spreadsheet.

I ask that all fees be waived as intend to use the requested records to further public understanding of public agencies and not for any commercial purpose. In the event you choose to impose fees, I request a detailed breakdown of the fees, including the hourly wage of each employee involved and an explanation justifying the employee hours required to fulfill the request.

Should you choose to reject this request or redact portions of responsive documents, I ask that you provide a detailed breakdown of the statutory exemptions and associated case law underlying your decision to withhold each/any portions from public review.

The requested documents will be made available to the general public, and this request is not being made for commercial purposes.

In the event that there are fees, I would be grateful if you would inform me of the total charges in advance of fulfilling my request. I would prefer the request filled electronically, by e-mail attachment if available or CD-ROM if not.

Thank you in advance for your anticipated cooperation in this matter. I look forward to receiving your response to this request within 5 business days, as the statute requires.

Sincerely,

Todd Feathers