The bill
Duplication Scoring Act of 2025
S. 2733, 119th Congress.
Sponsored by
Sen. Paul, Rand [R-KY]
ID: P000603
Follow the money
The bill
S. 2733, 119th Congress.
The sponsor
Every bill has someone who introduced it. That name is where the paper trail starts.
The money
20 itemised contributions to this sponsor, pulled from FEC filings.
The alignment
This bill's text tracks the "Department of Labor and Related Agencies" section, p. 630-632 of the Mandate for Leadership.
Track this bill's progress through the legislative process
Latest Action
Placed on Senate Legislative Calendar under General Orders. Calendar No. 566.
September 13, 2026
📍 Current Status
Next: The bill will be reviewed by relevant committees who will debate, amend, and vote on it.
1. Introduction: A member of Congress introduces a bill in either the House or Senate.
2. Committee Review: The bill is sent to relevant committees for study, hearings, and revisions.
3. Floor Action: If approved by committee, the bill goes to the full chamber for debate and voting.
4. Other Chamber: If passed, the bill moves to the other chamber (House or Senate) for the same process.
5. Conference: If both chambers pass different versions, a conference committee reconciles the differences.
6. Presidential Action: The President can sign the bill into law, veto it, or take no action.
7. Became Law: If signed (or if Congress overrides a veto), the bill becomes law!
**Duplication Scoring Act of 2025 (S. 2733): A House, MD-Style Diagnosis**
**Main Purpose & Objectives:** Ah, the Duplication Scoring Act of 2025—because nothing says “efficient government” like adding another layer of bureaucracy to *prevent* bureaucracy. Sponsored by Senators Paul and Hassan, this bill mandates that the Government Accountability Office (GAO) play bureaucratic whack-a-mole with every reported bill, scanning for signs of redundant federal programs like a hypochondriac checking WebMD for symptoms of government waste. The stated goal? To force the Comptroller General to analyze legislation *before* it becomes law, identifying whether it creates new programs that duplicate or overlap with existing ones already flagged in GAO’s annual duplication and overlap reports. In other words: let’s hire an auditor to tell us we’re about to repeat the same stupid mistake we’ve made 47 times before. How novel.
**Key Provisions & Changes to Existing Law:** The bill amends Section 719 of Title 31, U.S. Code, to require the GAO to assess every “covered bill or joint resolution” (i.e., any public bill reported by a congressional committee—yes, even the useless ones) for risk of creating a “new duplicative or overlapping feature.” If the GAO smells redundancy, it must: - Identify the offending program, its location in the bill, and which prior GAO report already warned about this exact flavor of stupidity. - Submit findings to the Congressional Budget Office (CBO) Director and the reporting committee. - Publish the results on GAO’s website, because transparency is great when it comes too late to stop the trainwreck. The CBO may then tack this analysis onto its cost estimate as a supplement—*if* the GAO delivers in time. If not, the CBO can still add it later, like a posthumous diagnosis. Riveting.
**Affected Parties & Stakeholders:** - **Congressional Committees:** Now forced to endure a pre-mortem on their legislative babies. Expect eye-rolling, delayed markups, and sudden discoveries of “urgent national priorities” that bypass scrutiny. - **GAO:** Promoted from historian of government failure to prophylactic nag. More work, no additional funding—classic unfunded mandate. - **CBO:** Gets to play editor-in-chief of legislative obituaries, deciding whether to slap a “DUPLICATION RISK!” sticker on a bill’s cost estimate. - **Taxpayers:** Theoretically benefit from less waste. Realistically, they’ll fund another report nobody reads while Congress ignores it and creates the duplicate program anyway—then blames the GAO for not shouting louder. - **Lobbyists:** Will now hire duplication consultants to game the scoring system, because of course they will.
**Potential Impact & Implications:** This is less a reform and more a bureaucratic placebo. It assumes that *knowing* we’re about to duplicate something will stop us from doing it—like telling a chain-smoker lung cancer is bad. The GAO has been flagging duplication for *decades*. Congress ignores it because duplication often serves patronage, committee turf, or the illusion of action. This bill adds theater to inertia: a shiny new process to lend the *appearance* of reform while the underlying disease—congressional cowardice, lobbyist capture, and the addiction to creating new programs instead of fixing old ones—rages untreated. In short: S. 2733 is a well-intentioned bandage on a gangrenous limb. It might slow the bleeding slightly, but unless Congress develops the spine to *act* on the GAO’s findings—or voters stop rewarding redundant pork—it’s just another expensive way to say, “We saw this coming. And we did it anyway.” Prognosis: Chronic legislative stupidity. Acute lack of accountability. Survival doubtful without radical behavioral change. Or a miracle. And we all know how Congress feels about miracles—unless they come with a ribbon-cutting and a press release.
Sen. Paul, Rand [R-KY]
Congress 119 • 2024 Election Cycle
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This bill has 1 cosponsors. Below are their top campaign contributors.
ID: H001076
Top Contributors
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Showing 46 nodes and 47 connections
Total contributions: $47
Showing top 19 donors by contribution amount
This bill shows semantic similarity to the following sections of the Project 2025 policy document.AI-enhanced analysis provides detailed alignment ratings.
AI Analysis:
"The Duplication Scoring Act of 2025 aligns with Project 2025's goal of reducing government waste and improving efficiency by identifying and preventing redundant federal programs, which overlaps with the policy's call to streamline overlapping workforce development programs and ensure outcome-based accountability. Both emphasize eliminating fragmentation and improving coordination across federal agencies."
— 597 — Department of Labor and Related Agencies Alternative View. While the federal government has a duty to promote economy and efficiency in federal hiring and contracting, and thus should base decisions on skills as opposed to degrees, it is not the federal government’s role to determine whether private employers may or may not include degree requirements in job descriptions and in their hiring decisions. The inappropriate reverence given to degree requirements is a byproduct of the federal government’s heavy subsidi- zation of BA degrees. Phasing down federal subsidies would be a better way to eliminate barriers to jobs for individuals without BA degrees. Federal Workforce Development Programs. Existing federally funded work- force development and training programs should be reassessed to ensure they are outcome-based and truly deliver value to taxpayers and job seekers. As of 2019, the federal government spent approximately $17 billion annually on 43 federal employment and training programs administered across nine federal agencies, many of which overlap with at least one other program. Many of these programs track only inputs or individuals served, not outcomes or outputs, and do not swiftly identify bad-actor grantees. The federal government should identify underperforming programs and eliminate or redirect that funding to programs with strong outcome-based metrics. l Evaluate and streamline workforce development programs, ensuring evidence-based outcomes. In its reauthorization of the Workforce Innovation and Opportunity Act (WIOA),14 Congress should evaluate and streamline the existing workforce development programs to ensure there is no overlap or fragmentation between programs. Congress should also ensure strong evidence-based outcomes for each program and tie federal funding for those programs to the outcomes achieved. l Review employment and training programs to ensure outcome- based metrics. DOL and other federal agencies with jurisdiction over employment and training programs should review their programs and utilize all available tools and authority to ensure these programs contain strong outcome-based metrics. To the extent that agencies have this authority, they should reevaluate funding for programs that do not meet those evidence-based and outcomes-based requirements. Finally, strong internal policies should be implemented to ensure bad-actor grantees are identified and sanctioned expeditiously. Federal Unemployment Insurance Program. In the post-pandemic land- scape, the federal government should restore the Unemployment Insurance (UI) program’s purpose with a particular focus on reestablishing program integrity and accountability. The Coronavirus Aid, Relief, and Economic Security (CARES) Act15 — 598 — Mandate for Leadership: The Conservative Promise unemployment programs were defrauded of hundreds of billions of dollars, includ- ing by state-sponsored hacking groups. Not all state agencies are yet through their backlogs of appeals and fraud cases; the recovery of lost funds has been minimal; and fraud has now spilled into the traditional UI programs. The CARES Act era drastically altered the entire UI ecosystem: The federal–state partnership shifted toward federal programs and funding, and the social insurance purpose of the program was disconnected as benefits were extended, expanded to more typically uncovered populations, and made exponentially larger. l Congress should enact bipartisan commonsense UI program reforms, including statutory authority for the Labor Office of Inspector General (OIG) to access all state UI records for the purposes of investigation and requiring state agencies to crossmatch applicants with the National Directory of New Hires. l Congress should also develop a framework (through commission of a congressional report to serve as a blueprint) of technical standards on broader tech topics like usability, state agency cybersecurity postures, data taxonomy standardization, and/or identity verification standards. l Congress should provide DOL with more reasonable enforcement tools for the UI system. Currently, DOL can either send a strongly worded letter or revoke the entire Federal Unemployment Tax Act (FUTA)16 tax credit, which would place an immediate 6 percent to 7 percent tax on all covered employers. l DOL should review all actual or planned procurements against the $2 billion (under the American Rescue Plan Act)17 for UI fraud detection, accessibility, and equity investments. These funds do not have appropriations timelines and have very minimal statutory descriptions of the intended purpose. DOL should also review and propose changes to improve state monitoring programs including developing evidence-based frameworks for evaluating the technical readiness and security postures of the state agencies; strengthen its relationship with the OIG and Government Accountability Office (GAO), and support continued development of fraud prosecution with DOJ, the Department of Homeland Security (DHS), and the financial services community; ensure administrative and IT funding is outcome-based; and gather and publish best practices from state officials, industry partners, and other vendors who deliver UI services.
AI Analysis:
"The Duplication Scoring Act of 2025 aligns with Project 2025’s goal of reducing redundancy and improving efficiency in federal programs, particularly in workforce development, by mandating GAO analysis of legislative proposals for overlap with existing efforts. While not specific to the Department of Labor, its focus on eliminating duplicative programs supports the broader objective of streamlining federally funded employment and training initiatives."
— 597 — Department of Labor and Related Agencies Alternative View. While the federal government has a duty to promote economy and efficiency in federal hiring and contracting, and thus should base decisions on skills as opposed to degrees, it is not the federal government’s role to determine whether private employers may or may not include degree requirements in job descriptions and in their hiring decisions. The inappropriate reverence given to degree requirements is a byproduct of the federal government’s heavy subsidi- zation of BA degrees. Phasing down federal subsidies would be a better way to eliminate barriers to jobs for individuals without BA degrees. Federal Workforce Development Programs. Existing federally funded work- force development and training programs should be reassessed to ensure they are outcome-based and truly deliver value to taxpayers and job seekers. As of 2019, the federal government spent approximately $17 billion annually on 43 federal employment and training programs administered across nine federal agencies, many of which overlap with at least one other program. Many of these programs track only inputs or individuals served, not outcomes or outputs, and do not swiftly identify bad-actor grantees. The federal government should identify underperforming programs and eliminate or redirect that funding to programs with strong outcome-based metrics. l Evaluate and streamline workforce development programs, ensuring evidence-based outcomes. In its reauthorization of the Workforce Innovation and Opportunity Act (WIOA),14 Congress should evaluate and streamline the existing workforce development programs to ensure there is no overlap or fragmentation between programs. Congress should also ensure strong evidence-based outcomes for each program and tie federal funding for those programs to the outcomes achieved. l Review employment and training programs to ensure outcome- based metrics. DOL and other federal agencies with jurisdiction over employment and training programs should review their programs and utilize all available tools and authority to ensure these programs contain strong outcome-based metrics. To the extent that agencies have this authority, they should reevaluate funding for programs that do not meet those evidence-based and outcomes-based requirements. Finally, strong internal policies should be implemented to ensure bad-actor grantees are identified and sanctioned expeditiously. Federal Unemployment Insurance Program. In the post-pandemic land- scape, the federal government should restore the Unemployment Insurance (UI) program’s purpose with a particular focus on reestablishing program integrity and accountability. The Coronavirus Aid, Relief, and Economic Security (CARES) Act15
AI Analysis:
"The bill focuses on preventing duplication in federal programs through GAO analysis, while the Project 2025 policy emphasizes performance appraisal reform and reducing legal barriers to employee evaluations. Both relate to government efficiency but address different aspects—operational redundancy versus personnel management—resulting in only weak thematic alignment."
— 73 — Central Personnel Agencies: Managing the Bureaucracy that would change regularly to depress cheating. President Donald Trump’s OPM planned to implement such changes but was delayed because of legal concerns over possible disparate impact. Courts have agreed to review the consent decree if the Uniform Guidelines on Employee Selection Procedures setting the technical requirements for sound exams are reformed. A government that is unable to select employees based on KSA-like test qualifications cannot work, and the OPM must move forward on this very basic personnel management obligation. The Centrality of Performance Appraisal. In the meantime, the OPM must manage the workforce it has. Before they can reward or discipline federal employees, managers must first identify who their top performers are and who is performing less than adequately. In fact, as Ludwig von Mises proved in his classic Bureaucracy,14 unlike the profit-and-loss evaluation tool used in the private sector, government performance measurement depends totally on a functioning appraisal system. If they cannot be identified in the first place within a functioning appraisal system, it is impossible to reward good performance or correct poor performance. The problem is that the collegial atmosphere of a bureaucracy in a multifaceted appraisal system that is open to appeals makes this a very challenging ideal to implement successfully. The GAO reported more recently that overly high and widely spread perfor- mance ratings were again plaguing the government, with more than 99 percent of employees rated fully successful or above by their managers, a mere 0.3 percent rated as minimally successful, and 0.1 percent actually rated unacceptable.15 Why? It is human nature that no one appreciates being told that he or she is less than outstanding in every way. Informing subordinates in a closely knit bureaucracy that they are not performing well is difficult. Rating compatriots is even consid- ered rude and unprofessional. Moreover, managers can be and often are accused of racial or sexual discrimination for a poor rating, and this discourages honesty. In 2018, President Trump issued Executive Order 1383916 requiring agen- cies to reduce the time for employees to improve performance before corrective action could be taken; to initiate disciplinary actions against poorly performing employees more expeditiously; to reiterate that agencies are obligated to make employees improve; to reduce the time for employees to respond to allegations of poor performance; to mandate that agencies remind supervisors of expiring employee probationary periods; to prohibit agencies from entering into settlement agreements that modify an employee’s personnel record; and to reevaluate proce- dures for agencies to discipline supervisors who retaliate against whistleblowers. Unfortunately, the order was overturned by the Biden Administration,17 so it will need to be reintroduced in 2025. The fact remains that meaningfully evaluating employees’ performance is a critical part of a manager’s job. In the Reagan appraisal process, managers were evaluated on how they themselves rated their subordinates. This is critical to
Showing 3 of 5 policy matches
Policy matches are calculated using a hybrid approach: initial candidates are found using semantic similarity between bill summaries and Project 2025 policy text, then an AI model (Llama 3.1 70B) provides detailed alignment ratings and analysis. Ratings range from 1 (minimal alignment) to 5 (very strong alignment). This analysis does not imply direct causation or intent.