Legislation Details

File #: 26-157    Version: 1
Type: Other Proposal Status: Discussion Agenda
File created: 7/31/2026 In control: Judicial Council
On agenda: 10/16/2026 Final action:
Title: Judicial Workload Assessment | Judicial Workload Study Update (Action Required)
Attachments: 1. 20261016-26-157 - updated 20260929_R
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Title

Title

Judicial Workload Assessment | Judicial Workload Study Update (Action Required)

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Summary

Summary

The Data Analytics Advisory Committee recommends that the Judicial Council adopt the 2026 Judicial Workload Study updated model parameters used as part of the formula for assessing judicial need in the trial courts. Applying the updated model parameters to the most recent three-year average of filings identifies a need for 231 additional judgeships across 22 superior courts. The full assessed need and prioritization details are presented separately in a companion report to the council, Report to the Legislature: 2026 Update of the Judicial Needs Assessment.

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Recommendation

Recommendation

The Data Analytics Advisory Committee recommends that the Judicial Council adopt the following Judicial Workload Study parameters, effective October 16, 2026, for use in evaluating statewide judicial workload and in the biennial judicial needs assessment to meet the requirements of Government Code section 69614(c)(2): 2

1.                     The updated judicial work year of 212 available working days for use in the Judicial Workload Study model, as described in the Analysis section below;

2.                     The updated judicial workday value of 401 minutes of case-related time per available working day for use in the Judicial Workload Study model, as described in the Analysis section below; and

3.                     The 2026 Judicial Workload Study updated caseweights for use in evaluating statewide judicial workload, as detailed in Attachment A, the proposed 2026 Judicial Workload Study Update-Draft Caseweights and Standards.

 

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Speakers

Speakers

Mr. Jake Chatters, Chair, Data Analytics Advisory Committee

Hon. Thomas E. Kuhnle (Ret.), Vice-Chair, Data Analytics Advisory Committee

Ms. Kristin Greenaway, Research, Analytics, and Data

Mr. Mustafa Sagir, Research, Analytics, and Data