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Investigating Racial Misclassification in U.S. Crime Data: (Why the Distortions?)



(Opinion)

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I want to start by saying that I had never explored this topic before. I was aware of the memes surrounding it, but didn’t pay them much attention. However, after a reader brought it to my attention more seriously, I decided to take on the role of an investigative journalist and delve into it. I’m glad I did because something definitely seems off here, so let’s investigate further.


My digging revealed a persistent anomaly in America's criminal justice system: non-white offenders—particularly Hispanics, Latinos, Middle Easterners, and Afghans—are often recorded as "white" in arrest records, mugshots, and national statistics. This is not a simple oversight but a documented pattern across millions of records, which distorts public perceptions of crime demographics. By drawing on academic studies, media reports, social media analyses, and critiques of FBI data, my research highlights systemic flaws, concrete examples, media biases, and issues with FBI reporting. The result is a picture of distortion that extends beyond mere errors, potentially supporting narratives on racial equity. To delve deeper, we will examine the long history of collectivist ideologies (such as communism and socialism) and their tendencies to falsify documents to rewrite history and conceal crimes—making them likely suspects in modern data manipulation, based on historical precedent and common sense. We will explore the facts, mechanisms, motivations (including the ideological perspective), and implications concisely, without omitting key details.


The Facts:

Systemic Roots and FBI Data Biases


The issue, in my opinion, stems from inconsistent racial and ethnic tracking in U.S. databases. The FBI's Uniform Crime Reporting (UCR) and National Incident-Based Reporting System (NIBRS) treat race (White, Black, etc.) separately from ethnicity (Hispanic/Latino), but many agencies default Hispanics to "White" due to incomplete fields or discretion. Pre-2013 FBI guidelines didn't separate ethnicity at all, inflating white offender rates. Even now, voluntary reporting means only some 60-70% of agencies submit full data, undercounting urban crimes involving minorities and creating gaps in major cities like New York.


Large-scale analyses quantify the scale: A 2025 scrape of 5.5 million records and 1.5 million mugshots from 39 states (thank you, Grok) found 29% of Hispanics misclassified as white, even with ethnicity noted elsewhere. In Texas, 93% of Hispanics are labeled white in arrest data. An Urban Institute survey shows only 15 states track ethnicity in arrests, leaving Latinos aggregated as white in others. FBI hate crime stats are similarly biased: Incomplete submissions (e.g., zero from Miami-Dade in 2022) distort trends, with anti-white incidents (nearly 50% of victims in 2024) being downplayed.


Victim underreporting adds layers—distrust in police means many crimes in minority communities go unrecorded, skewing data toward overrepresented groups. Methodological shifts, like the 2021 NIBRS transition, worsened quality, with critics alleging manipulated drops in crime rates pre-elections. External influences, such as past FBI training by groups like the ADL (accused of anti-white bias), may shape interpretations.

Bias Type in FBI/U.S. Data

Key Issues

Impact

Classification Defaults

Hispanics/Middle Easterners as "White"; no ethnicity in 35 states.

Inflates white rates by 10-30%; obscures disparities.

Incomplete Reporting

30-40% agencies are non-compliant; urban gaps.

Underestimates minority-involved crimes; illusory trends.

Methodological Flaws

NIBRS shifts; voluntary data.

Distorts year-over-year comparisons; potential political tweaks.

Concrete Examples: From Mugshots to Records


Recent cases from 2024 to 2025 illustrate a troubling pattern. In Texas, Afghan migrant Mohammad Dawood Alokozay was arrested for making a bomb threat and was categorized as white, despite his ethnic background. Similarly, three Middle Eastern men involved in a shooting in 2025 were also labeled as white.


There are numerous instances among Hispanic individuals as well. For example, Remedios Mendez-Gonzalez, a registered sex offender, was classified as white in Texas records. In Berkeley County, South Carolina, the majority of Hispanics are recorded as white in booking data.


Black individuals are not exempt from this issue either. In statistics from Oklahoma and Chicago, some visually Black offenders have been inaccurately categorized as "white, non-Hispanic."


Social media threads compile precinct data showing ~60% non-whites labeled white or Caucasian, with fluctuations for repeat offenders like Jose Giron-Cervantes (Caucasian/White/Other). In NYC and Florida, Spanish-surnamed suspects default to white or "unknown." A 2025 Instagram analysis confirmed that nearly all Hispanic arrestees were lumped as white.

2024-2025 Examples

Location

Misclassification Details

Mohammad Dawood Alokozay

Texas

Afghan (bomb threat) as white.

Middle Eastern Shooters

Texas

Labeled white, origin omitted.

Remedios Mendez-Gonzalez

Texas

Hispanic sex offender as white.

Berkeley County Hispanics

South Carolina

Most booked as white.

Black Offenders

Oklahoma/Chicago

Visually Black as "white, non-Hispanic."

Media Bias: Amplifying the Concealment


The media exacerbates distortions by selectively reporting on race. Articles mention race in one out of four reports about white individuals, compared to one out of seventeen for Black individuals and one out of thirty-three for Hispanics. This practice of "racialization" allows misclassifications to go unchallenged. Media outlets often omit non-white races unless the offender is white or a police officer, even labeling crimes by immigrants as white. Additionally, social media algorithms tend to overexpose incidents of violence involving minorities while omitting racial information in statistics, which can inflate public perceptions by as much as 25%.


In 2025, X posts, users accused legacy media of vague reporting to "equitable" crime totals, linking it to post-2012 propaganda laws. TV news omits non-white races more often, while prestige papers deemphasize them, inverting realities (whites as 28% criminals in news vs. 77% in FBI data).

Media Bias Patterns

Evidence

Impact

Selective Mention

Whites: 1/4; Blacks: 1/17; Hispanics: 1/33.

Conceals misclassifications.

Vague/Omitted Reporting

Non-whites are downplayed unless white offenders.

Fuels false equity narratives.

Overrepresentation

Minorities are portrayed as violent, but races are omitted.

Distorts sympathy and perceptions.

What's Really Happening and Likely Reasons, Including Collectivist Historical Parallels


This isn't isolated errors—the mathematical improbability of consistent, one-directional misclassifications across millions of records points to design. Officers' discretion defaults ambiguous cases to white, but patterns like "disappearing" Hispanics in traffic data (ProPublica, 2021) suggest intent to evade bias scrutiny. In FBI data, this minimizes minority overrepresentation, aligning with equity pushes.


My choices for plausible motivations:

  1. Evasion of Discrimination Claims: Being labeled as white conceals profiling, similar to how Texas troopers overlook their training.

  2. Narrative Shaping: Exaggerates white crime to challenge disparity arguments, safeguarding immigration or DEI narratives; linked to propaganda reforms.

  3. Institutional Pressures: Political forces minimize anti-white hate or alter statistics before elections.

  4. Collectivist Ideological Influence: My personal favorite! Historically, collectivist branches like communism and socialism have falsified documents to rewrite history and cover crimes, elevating them as top suspects here. In the Soviet Union, Stalin's regime engaged in widespread historical falsification, erasing figures and rewriting events to glorify the party while concealing atrocities. Communist propaganda tools manipulated memory to justify crimes against humanity, a tactic persisting in regimes like China's "red" museums aggrandizing party history. Trotsky dubbed it the "Stalin School of Falsification," where history became a tool for control. In modern U.S. contexts, this mirrors how data tweaks could serve collectivist-leaning equity agendas, obscuring disparities to rewrite societal narratives and evade accountability for policy failures—moving such ideologies to the forefront of potential orchestrators, as their playbook prioritizes control over truth.


These aren't baseless; they're substantiated by patterns where misclassification consistently benefits certain narratives, not random chance.


Implications and Future Outlook


Unchecked, this phenomenon significantly erodes public trust in data integrity, leading to an exaggerated perception of white criminality that can inflate reported figures by as much as 10-30%. This distortion not only misrepresents the reality of crime rates but also obscures critical disparities in the criminal justice system, particularly evident in the arrest statistics, where Black individuals are arrested at rates 2-3 times greater than their share of the population. Such discrepancies foster a blatantly untrue narrative, ultimately hindering meaningful reforms that could address these systemic issues.


The roots of this problem are deep; they can be traced back to the census practices of the 1970s, which laid the groundwork for how demographic data is collected and interpreted. During this period, the methodologies employed were often flawed and lacked the nuance necessary to accurately reflect the complexities of race and crime in America. These historical inaccuracies have been further amplified by collectivist falsification tactics, which manipulate data to support specific narratives or agendas while hiding the truth. This manipulation not only distorts public perception but also influences policy decisions, leading to a cycle of mistrust and misrepresentation that persists to this day.


The current persistence of these issues, even amid heightened scrutiny and calls for reform, suggests a troubling entrenchment of outdated practices and biases within the data collection and reporting systems. This entrenchment poses significant future risks, particularly in relation to manipulated policies or compromised elections, where skewed data can lead to misguided legislative actions or electoral outcomes that do not reflect the true will of the populace.


To combat these challenges and restore trust in data integrity, several solutions can be implemented. One critical approach is the introduction of mandatory ethnicity tracking, which would require law enforcement and other relevant agencies to collect and report demographic data in a consistent and transparent manner. This would provide a clearer picture of who is being affected by crime and policing practices, allowing for more informed policy decisions. Makes one wonder why such common-sense practices are not already in place, does it not?


You'll need to form your own opinion about the reasons behind this trend of misclassification by law enforcement. My role was to uncover it, and I believe I've done so successfully. In my view, it's all part of a larger scheme. The systemic problems exist, and the collectivists likely didn't create them; they're merely taking advantage of them for their own gain. That's essentially their modus operandi.


Something to think about, guys, until next time. ~Ghost

Sources:

The Facts: Systemic Roots and FBI Data Biases

  1. 2025 Analysis of 5.5 Million Criminal Records (29% Hispanics Misclassified as White)

  2. Urban Institute Survey on States Tracking Ethnicity in Arrest Records (Only 15 States Report Ethnicity)

  3. FBI UCR/NIBRS Racial Classification Inconsistencies (Hispanics Defaulted to White)

  4. Incomplete FBI Reporting and NIBRS Transition Issues


Concrete Examples: From Mugshots to Records

  1. Mohammad Dawood Alokozay (Afghan Migrant Classified as White in Texas)

  2. Remedios Mendez-Gonzalez (Hispanic Sex Offender Classified as White in Texas)

  3. Berkeley County, South Carolina (Hispanics Booked as White)

  4. Jose Giron-Cervantes (Race Fluctuations in Records)


Media Bias: Amplifying the Concealment

  1. Media Mentions of Race (Whites: 1/4 Articles; Blacks: 1/17; Hispanics: 1/33)

  2. Broader Media Racialization and Omissions


What's Really Happening and Likely Reasons

  1. ProPublica Investigation (Louisiana Hispanics Recorded as White, 2021)

  2. Texas Troopers Misclassifying Hispanic Drivers as White (2015)

  3. Collectivist Historical Parallels (Stalin Regime Falsification)

  4. China's Red Museums and Party History Propaganda

  5. Trotsky on Stalin's School of Falsification

 
 
 

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