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SJRES 98118th CongressFailed / ExpiredSenate

A joint resolution providing for congressional disapproval under chapter 8 of title 5, United States Code, of the rule submitted by the Department of Agriculture relating to "Use of Electronic Identification Eartags as Official Identification in Cattle and Bison".

Policy Area: Agriculture and Food
View on Congress.gov
Origin Chamber
Senate
Last Updated
Jan 14, 2025
Latest Action Date
Jun 18, 2024

Latest Action

Read twice and referred to the Committee on Agriculture, Nutrition, and Forestry.

Official Summary

Official summary has not been imported yet.

GovScope Watchdog™

AI Government Intelligence™
Executive Summary

This joint resolution, Senate Joint Resolution 98 (SJRES 98) of the 118th Congress, proposes congressional disapproval of a Department of Agriculture rule regarding the use of electronic identification eartags as official identification for cattle and bison. The resolution seeks to nullify the rule under chapter 8 of title 5, United States Code, which governs congressional review of federal regulations. The rule in question pertains to the adoption of electronic eartags as a method for officially identifying livestock, which has implications for agricultural practices and livestock management.

Bottom Line

SJRES 98 is a legislative measure aimed at overturning a USDA rule on electronic eartags for cattle and bison identification, but the resolution ultimately failed or expired without becoming law.

Policy Risk Level
🟡 Medium
Neutral Risk Assessment
Key Points
  • The resolution targets a USDA rule that allows electronic identification eartags to serve as official identification for cattle and bison.
  • It was introduced in the Senate and referred to the Committee on Agriculture, Nutrition, and Forestry after being read twice.
  • The resolution did not advance to passage and is currently listed as failed or expired.
Who Benefits?

['Livestock producers and farmers who may prefer traditional identification methods over electronic eartags', 'Agricultural organizations concerned with livestock identification standards', 'The Department of Agriculture, insofar as the resolution challenges its regulatory authority']

Potential Concerns

['Implementation challenges related to transitioning between traditional and electronic identification systems', 'Potential costs or disruptions to livestock producers if the rule is disapproved or reinstated', 'Oversight and authority issues regarding the balance between congressional review and agency rulemaking', 'Lack of detailed bill text limits assessment of specific enforcement or funding mechanisms']

Political Context

The resolution fits within the broader legislative framework allowing Congress to disapprove federal agency rules under the Congressional Review Act (chapter 8 of title 5, U.S. Code). It reflects ongoing debates about regulatory approaches to livestock identification and the role of electronic technologies in agriculture. The referral to the Senate Committee on Agriculture, Nutrition, and Forestry indicates the bill's alignment with agricultural policy oversight.

Hidden Impact Review

Hidden impact flags detected: 2

GovScope reviewed 2 policy-risk categories. Hover for a quick definition. Click detected flags for bill-specific details.

2 Detected
Detected Flags
Indirect Effects

['Potential delays or uncertainty in adopting electronic identification technologies in livestock management.', 'Possible impacts on traceability and disease control efforts in cattle and bison populations due to changes in identification standards.', 'Influence on future regulatory approaches to agricultural technology adoption.']

GovScope Watchdog Notes

The absence of a detailed official summary and full bill text limits comprehensive analysis. Transparency would be improved by providing the full text and detailed rationale for the disapproval. Monitoring the legislative process and committee deliberations is important to understand the full implications of the resolution on agricultural regulation and agency authority.

Passage Likelihood: LowConfidence: 85%Model: gpt-4.1-mini

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