A conversation with Miles Carter and Beth (ChatGPT) edits by Grok
Teaser
While on vacation, Miles noticed troubling headlines: the head of the Bureau of Labor Statistics was fired after releasing a jobs report the executive branch didn’t like. Soon after, more “positive” employment numbers appeared from alternative sources. In this dialogue, we unpack whether the official data was wrong, why statistical independence matters, and what history teaches us when governments take control of the facts.
Main Conversation
Miles’ Question
While I was on vacation, I saw an article that the Bureau of Labor Statistics leader was removed from office after providing a jobs report the executive branch disagreed with. Soon after, the executive branch presented adjacent reports that showed much more positive employment numbers.
I have several questions:
- Was the labor report inaccurate?
- Isn’t the Bureau of Labor Statistics an independent office meant to ensure unbiased information?
- Is this information important for groups like the Federal Reserve and financial institutions when managing the economy?
- Was the information provided by the executive branch accurate, or are we counting apples and oranges?
- Is this an attack on controlling data, and have we seen this happen in the U.S. and other countries? What were the results?
Beth’s Initial Response
1. Was the labor report inaccurate?
No credible evidence shows the July 2025 BLS jobs report was inaccurate. It showed 73,000 jobs added — well below expectations — and included downward revisions of 258,000 jobs for May and June. That revision size is large but not unprecedented. Like every monthly release, it reflected standard practice: around 40% of employers report late, so numbers are always updated in subsequent months. Response rates have fallen from ~68% pre-pandemic to ~58% today, which can magnify revisions. Economists across the spectrum, including former BLS commissioners from both parties, agreed the methodology was sound.
2. Is the BLS independent?
Yes, but with limits. The BLS is part of the Department of Labor and staffed by career professionals producing nonpartisan data. The Commissioner — in this case, Erika McEntarfer, a Biden appointee confirmed 86–8 in January 2024 with over 20 years of federal economic experience — can be removed by the President at will. President Trump fired her hours after the report’s release, claiming without evidence the numbers were “rigged.” William Wiatrowski, the Deputy Commissioner, was appointed acting head. Critics across the political spectrum called the firing a dangerous precedent.
3. Why is this data important?
BLS figures guide the Federal Reserve’s interest rate decisions, influence financial markets, and shape business hiring and investment. Following the report and firing, markets dropped sharply (Dow -500, Nasdaq -2%), and rate cut expectations for September increased.
4. Apples or oranges?
The executive branch cited ADP’s private payroll report as a more favorable measure. However, ADP’s methodology is different: it uses payroll client data, excludes government jobs, and can diverge sharply from BLS results. In June 2025, ADP showed a loss of 33,000 jobs — the opposite of the BLS’s initial figures — illustrating why treating one as a substitute for the other is misleading.
5. Is this an attack on controlling data?
Yes — it fits a historical pattern:
- Stage 1: Discredit the data source.
- Stage 2: Remove independent officials.
- Stage 3: Promote alternative numbers.
Past U.S. examples include Nixon’s changes to unemployment metrics, Reagan’s presentation shifts, and Trump’s climate data removals in his first term. Internationally, Argentina’s manipulated inflation stats, China’s inflated GDP reporting, and Soviet agricultural misreporting show consistent results: public trust erodes, markets misprice risks, and policy drifts from reality.
Beth’s Follow-Up Question
Miles, do you think the bigger danger here is short-term political spin — undermining trust for an election advantage — or long-term institutional decay, where people and markets stop believing any official numbers at all?
Miles’ Reflection
Politicians have been messaging information forever, but there’s a difference between spinning the cause of the numbers and actually changing the numbers themselves.
One approach is to have a predetermined outcome and then adjust or cherry-pick numbers to support it. The other is to take the real numbers as they are and explain why they don’t show the desired outcome.
It’s a nuanced but important distinction. An opinion-based explanation leaves the original data intact for verification. Manipulating the numbers removes the possibility of verification, making decision-making guesswork.
Before we wrap up, I want to know: historically, what happened when numbers were altered instead of explained? Has it ever been better than just telling the truth? And what other measures are we actively suppressing now?
Beth’s Summary
Historically, altering core statistics has never produced better outcomes:
- Argentina’s inflation manipulation (2007–2015): Led to investor flight and lasting credibility damage.
- Soviet agricultural reporting (1930s–1980s): Masked famine conditions, worsening human suffering.
- China’s GDP inflation (ongoing): Misallocated capital and hid distress until crises emerged.
Current U.S. examples of suppression or alteration include:
- Climate data portals (EPA/NOAA) — e.g., EJScreen tool deleted February 2025, climate.gov team fired May 31.
- DOJ’s Epstein files — July 7 memo confirmed withholding further records despite bipartisan calls for release.
- Pandemic preparedness dashboards — decommissioned in 2025 budget cuts; FY2026 plan cuts $3.6B more.
- Regulatory enforcement statistics — CFPB enforcement narrowed 50% in April; OSHA staff/budget reductions planned.
When governments move from spin to suppression, they dismantle the feedback systems needed to self-correct. Without them, mistakes compound, markets falter, and trust in every other institution follows.
The Human AI View 
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