Pays Mobility Blueprint up to $67,500 for mapping to find prospective early childhood students

Mobility Blueprint will build a mapping tool that uses location data to identify prospective students by zip code, age group and school zone, find currently enrolled students, and locate multi-family and affordable housing. It also includes training. The Early Childhood Development Department oversees it, from August 19, 2024 through June 30, 2025. The work period began before this Board vote.

Plain-English summary written by AI from the official text. AI summary · amounts checked against official text

Vendor / partner: Mobility Blueprint · Austin, TX
Action: New agreement
Category: Technology
Term: Aug 19, 2024 – Jun 30, 2025
This vote: $67,500
Funding: "First 5" Measure AA
Resource / site: 9186-910
Vendor no.: 009156
Presented by: Chief Academic Officer
File: 24-2037 · agenda T.-53
Outcome: Adopted on the General Consent Report, Sep 11, 2024

Official text

Ratification by the Board of Education of a Services Agreement 2024-2025 by and between the District and Mobility Blueprint, Austin, TX, for the latter to create Student Prospects - Oakland USD that will utilize GIS mapping to Identify prospective students by zip code, age group, school zone and district boundary; Identify currently enrolled OUSD students; Identify Census Block Groups and view American Community Survey information; Locate multi-family and affordable housing and offer multiple levels of training, with schedules coordinated with District identify locations and dates that maximize attendance, via Early Childhood Development Department, for the period of August 19, 2024 through June 30, 2025, in an amount not to exceed $67,500.00.

History

Sep 11, 2024 Adopted on the General Consent Report

This is an independent project created to provide transparency to the OUSD Community, and is not affiliated with Oakland Unified District. All data used to create the Consent Report Tracker is made public by Legistar, OUSD's official platform for posting legislative records. Plain-English summaries are written by AI with narrow parameters based upon the official text of the reports. Read about how all this works.