349 points by inaros 1 days ago | 373 comments on HN
| Moderate positive
Contested
Low agreement (3 models)
Editorial · v3.7· 2026-03-15 23:01:43 0
Summary Information Integrity & Institutional Trust Advocates
MIT Sloan's article examines consequences of unreliable US economic data for policy and institutional systems, advocating implicitly for data integrity as a precondition for informed governance and human welfare. The content engages substantively with how information systems affect collective decision-making, rights protection, and social order, while the institutional platform provides free access to expert economic analysis supporting public education and informed citizenship.
Rights Tensions2 pairs
Art 12 ↔ Art 19 —User privacy (Article 12) through routine analytics tracking versus freedom of expression and information (Article 19) through open publication; the site prioritizes public information access over user privacy notification.
Art 26 ↔ Art 25 —Right to education (Article 26) via free content access versus adequate standard of living (Article 25) affected by policy based on unreliable data; the article advocates for data reliability as prerequisite for welfare-supporting policy, but does not address structural barriers to education access in its discussion.
The phrase "when US data becomes unreliable" is misleading in one sense: for many years political manipulation of economic data has screwed things up.
Calculation of unemployment and real debt has seldom matched the norms of most other western countries. Add military (often black budgets) spending without much oversight or accurate accounting.
The wealthiest people in the USA are now in the mode of grabbing what they can while the 'grabbing is still good.' Without this immoral looting, our government could do a better job of protecting US citizens as our empire collapses.
"The change may cause policymakers to misjudge the economy’s health, investors to lose confidence in the reliability of the data, and the public to disengage from participating in official measures altogether."
Many neoliberal Western countries with good data have completely fumbled their economies post-GFC and post-Covid, just look at Canada's disastrous GDP per capita growth.
One of the things I do like about the US, and that I think is a reason for America's ability to meet the challenges this country faces is that it has good data collection and aggregation mechanisms: from the seemingly-banal surveys and so on to satellite remote-sensing.
There's three more years to go but afterwards (and perhaps even post the mid-terms) we should be able to hammer back some of this nonsense like being upset about job reports not showing favourable information and so on. Good information allows good decision-making and it's important we don't break that. Hopefully the current surge of low-quality corrupt executive choices isn't met by a counter-surge that kicks out people like Jerome Powell because he's a multi-millionaire capitalist or whatever.
I think it won't be. The establishment folks are mostly sensible. It's the new crop of "no property tax" and "no income tax for tips" and "no tax for under $100k earners" and so on that makes me worried, but I'm hoping it will all settle down soon.
We'll have to find better surveying methods than the phone surveys but provided #2 and #3 are solved in the article, which is just a matter of switching the admin, then we should be able to.
- When a measure becomes a target, it ceases to be a good measure.
I have no idea which is more relevant here. Looking at the first one, my whole life people have been complaining that the measures that get touted in political discourse don't reflect quality of life. So if we stop looking at those as measures because they cease to be reliable, maybe they stop getting myopically optimized and we can get less myopic about what we prioritize in aggregate.
But looking at the second one, I've also wondered whether those measures really do reflect typical quality of life, and it's just that the people doing worse than typical will always see the measure as the wrong measure. So then we'd be losing the ability to prioritize actually useful things.
In my heart though, I kinda lean towards the first one. I've been in enough orgs where "the dashboard goes up" is incentivized to the detriment of the unmeasurable things that actually matter to the org.
People in Florida, when I tell them about my background working with data, often scoff and claim that the data can be changed to spread lies. They have a government who arrested a data scientist when she published information about Coronavirus. This is prevalent across all of America, especially after DOGE, who encourage fraud so the data supports their political interests.
I think the reliability problem is very bad. It's not just that the US government is encouraging fraud, it's also that the average American hates AI and data science. Usually, the public would prefer reliable data, but in this case, Americans seem to prefer corruption just to spite the AI.
We're certainly living in a post-truth country. By vilifying higher education, the assumption that Americans can interpret data is challenging. Therefore, Americans are consuming biased information in their online bubbles because their media is comfortable with fraudulent data.
A concrete example of what happens whenUS economic data becomes unreliable is employment numbers. At the end of 2025, the government couldn't produce any data because of the government shutdown. Most quants and analysts utilized ADP numbers instead. A few years ago, the ADP payroll numbers and the projections by the government were perceived as aligned. This is no longer the case, and most traders rely more on ADP indicators for things like the unemployment rate.
Speculating on what other data is fraudulent, I suspect that real Gross Domestic Product (GDP) will become meaningless. It was supposed to be an indicator for economic wellbeing but now best describes wealth inequality. Nominal GDP is a slightly better measure because it adjusts for things like inflation but it's based on government produced data.
Lastly, there is widespread fraud in climate data in order to deny climate change. The data feeds into economic models and affects property values and insurance rates. I have personally received gag orders from government agencies from both the US and Europe for publishing environmental data.
The article says: US Government surveys are suffering from poor response rates and decreasing budgets so business leaders will have to explore other options to improve reliability.
This thread says: American Empire is dying and the world is a fraud.
Are all of you bots? Is apocalyptic cynicism this widespread? Fact is that most of the world already gets by with a fraction of the economic data we produce. We have enjoyed an incredibly high standard for breadth, depth and quality of data and it's now proving unsustainable. Political manipulation thus far remains a specter to be wary of, but there's no indication any headline numbers are inaccurate. The downstream affects on policy are equally off in the distance maybe never to appear.
Change in Data Sources Led to Lower Inflation Reading
Excerpts:
“On its merits, you can defend the change,” said Omair Sharif, founder of Inflation Insights, a forecasting firm. “Optically, it’s just not a good look in an environment when people are worried about political interference.”
Mr. Sharif said he did not believe the change was politically motivated. But Courtney Shupert, an economist at MacroPolicy Perspectives, another forecasting firm, said such decisions undermine public confidence in the statistical system.
“It seems like we are moving to more of a vague, uncertain, cloudy data quality environment that is going to make market participants less confident in the data that we do receive,” Ms. Shupert said.
That will lead to serious problems, as in the case of China, underestimating threats lead to losing edge, from EV to robots and other vital tech, and without experts to ground policy in reality, the country risks making erratic market moves and failing to spot risks from adversaries like China or Russia.Add to that inexperienced staff in the administration who makes the U.S. easier to manipulate.
The books Why Nations Fail and The Narrow Corridor (by two of the winners of past years Nobel Economics award, both books are a simple thesis and lots of historical examples IMHO) will have to be updated to include this and other current events in the USA. This is one of many aspects mentioned in both books.
It's sad how counter productive the unreliable economic data is. The people buying groceries know that things are more expensive. And the people looking for a job know how hard it is to find work.
But this administration wants to say everything is fine, and fires those that say otherwise. So now unemployment seems under control even though it's not great.
Now the Fed, with their dual mandate to maintain a healthy labor market and control inflation, is considering raising rates. If it turns out the job market was much worse than we realized, raising rates could tank the economy more than it already is tanking. All because they wanted to pretend everything is fine.
It seems nobody has posted this, but the only reason why this would ever be an issue is the principal–agent problem. When a representative democracy has a significant divergence between the representatives and the people being represented, we encounter this:
This ratchet effect of partially righting the ship every four years followed by drunken sailors YOLOing further into a reef because the ‘responsible party’ didn’t fix things fast enough is unsustainable. No clue how it ends but it’s so much easier to destroy things than it is to build them, so the builders are always at a distinct disadvantage.
The frustrating thing about the empire collapse is that it doesn't need to happen. There are still tons of highly energized and ostensibly disciplined and competitive people here. It's just that the production base was sold off to foreign lands and the aesthetic and moral project of "America" was effectively discontinued, for reasons unclear.
> just a matter of switching the admin, which we should be able to
I wish I shared your optimism. Being unable to change the admin has been the default state. The recent few centuries have been an exception. It's a big ship that we need to turn here. Might take longer than we think if we can manage it at all.
> They started out innocuously and predictably enough. Bitcoin or ethereum? Virtual reality or augmented reality? Who will get quantum computing first, China or Google? Eventually, they edged into their real topic of concern: New Zealand or Alaska? Which region would be less affected by the coming climate crisis? It only got worse from there. Which was the greater threat: global warming or biological warfare? How long should one plan to be able to survive with no outside help? Should a shelter have its own air supply? What was the likelihood of groundwater contamination? Finally, the CEO of a brokerage house explained that he had nearly completed building his own underground bunker system, and asked: “How do I maintain authority over my security force after the event?” The event. That was their euphemism for the environmental collapse, social unrest, nuclear explosion, solar storm, unstoppable virus, or malicious computer hack that takes everything down.
Canada’s population has increased at an astonishing rate, I wonder if that affects the per capita numbers. If you have the same industry in 2011 and 2026 but population went from 35 million to 42 million, per capita the numbers look terrible
>They have a government who arrested a data scientist when she published information about Coronavirus
That was fake news:
In May 2020, Jones was terminated from her position managing the team that created Florida's ArcGIS COVID-19 dashboard after being repeatedly reprimanded for sharing the department's work online without authorization. Jones alleged instead that she was told to manipulate the dashboard's data and that her firing was retaliation for her refusal. The OIG exonerated state health officials, finding her allegations to be unsubstantiated and unfounded. Jones later posted on social media a forgery of the dismissal letter from the Florida Commission on Human Relations, such that it appeared that her complaint had been validated.
In December 2022, she signed a deferred prosecution agreement admitting guilt to unauthorized use of the state's emergency alert system on November 10, 2020, which resulted in her home being searched under warrant by state police in December 2020. The execution of the warrant with armed police, widely referred to as a raid, was due to a 2016 battery charge against Jones by the Louisiana State University police. In 2023, Jones pled no-contest to a 2019 charge of cyberstalking a former Florida State University student. She was fired from both institutions.
Can you tell us a bit more about the gag orders? I find it fascinating that all the discussion about climate change has largely disappeared after LLMs became mainstream, and the idea that state actors may be suppressing data is equally fascinating/terrifying.
the answer is reliable money. how much money would you pick up a verified 1 minute survey from the real u.s. government for? I'd do it for $5. (=$300 per hour) and hope for as many calls as possible.
For comparison purposes the U.S. budget is about $20,000 per person ($7t budget, a bit under 350m people), so the government could definitely pay you to answer their "spam" calls. (While mandating that first parties show that it is the real U.S. government and not a spammer.)
So it would be your actual first party telephone showing "Answer this real call from the U.S. government for $5 instantly, 1 minute average call time."
I think that would be a good way to get good data fast. What do you think? (At the same time, impersonating the U.S. government would remain illegal, and the first party would ensure the payment is real.)
Citing Rebekah Jones in your argument is the opposite of convincing. She forged documents related to her firing to make her appear more sympathetic. She has been adjudicated guilty of cyberstalking and misuse of the state’s emergency notification system, and I haven’t seen a credible defense against those accusations. She’s a fraud, and many in the media uncritically boosted her claims because they shared her political aims. That people still cite her is proof of the old adage that a lie can travel across the world before the truth can lace its boots.
And the fact that they're different between the US and other countries, and between other countries and other-other countries is well recognized; "International unemployment rates: how comparable are they?":
Even stacking government with loyalist appointees is, to a certain extent, returning to 'the old ways' before reforms were enacted to clamp down on the practice:
The establishment has been replaced by MAGA and The Heritage Foundation extremists. The "data collection", surveys, remote-sensing etc are things they all want to get rid of and are doing so.
Here's one article from last year about climate datasets being disappeared,
I really don’t like people bashing my state, especially when they’re repeating made-up bullshit. Do you just believe anything negative you read as long as it fits your views?
Unfortunately America has pretended everything was fine for at the very least 130 years now, arguably longer, and we have allowed an extremely predatory, toxic, parasitic, fraudulent, thieving and lying set of people plunder not only the money through "money printing" but also plunder the very government through various types and forms of judicial and legislative authoritarian fraud, which was then installed in people's minds through education as the acceptable norm even though there was nothing "democratic" of free, let alone Constitutional about it.
The US fired many of its government-employed economists. The administration head tried to fire people at NOAA his first term, until he got a yes-head. Data was deliberately buried in a mad rush the first few weeks and months of 2025. I'm not quite sure Mr. Sharif's opinion is well-founded given the known facts.
Really, when you look at it first hand over more than just a few decades, what's all the debate about?
What happens is what you're seeing right now.
Same as ever.
Any unflattering statistics still existing that were originally designed to reveal, were reversed during applicable times of desperation in case they revealed too much.
Leaving almost nothing that does not serve to conceal instead, often more well crafted to conceal the exact thing expected and relied upon to be revealed.
Article directly engages with right to education and human development. MIT Sloan's mission emphasizes developing 'principled, innovative leaders' through education. Content itself—analysis of economic systems—exemplifies educational value of examining complex institutional practices. Implicit advocacy for education's role in enabling informed citizenship and human potential.
FW Ratio: 56%
Observable Facts
MIT Sloan explicitly states mission to 'develop principled, innovative leaders who improve the world.'
Article byline credits 'Betsy Vereckey' and 'Roberto Rigobon' (faculty member, Society of Sloan Fellows Professor), indicating faculty research contribution to public knowledge.
Content published in 'Ideas Made to Matter' platform supports free educational dissemination.
Sidenote includes faculty profile link enabling readers to learn about expert credentials.
Inferences
Educational mission and diverse program offerings demonstrate institutional commitment to developing human potential through formal education.
Faculty engagement in public-facing research and analysis supports the view that education extends beyond degree-seeking students to inform public discourse.
Free publication of expert analysis supports right to education by enabling access to advanced economic thinking without tuition barriers.
Focus on 'improving the world' through leader development reflects implicit belief in education's role in human flourishing and social progress.
Article directly engages with freedom of expression and information through focus on reliability of economic data. Unreliable data impairs public's ability to receive accurate information. Content examines how data integrity affects informed public discourse on economic policy. This implicitly advocates for reliable information as prerequisite for meaningful expression and public understanding.
FW Ratio: 63%
Observable Facts
Article published by MIT Sloan faculty and journalists without apparent editorial restrictions.
Content appears in 'Ideas Made to Matter' section, explicitly framing publication as knowledge dissemination.
Share functionality enables readers to distribute article across social media platforms.
Article examines 'what happens' when economic data becomes unreliable, inviting critical examination of information systems.
No visible censorship, paywalls, or viewpoint-based access restrictions on provided content.
Inferences
Publication of analysis questioning data reliability demonstrates institutional commitment to free examination of institutional practices.
Open access and shareability infrastructure supports freedom of expression for both institution and readers.
Focus on data integrity as systemic concern reflects implicit advocacy for reliable information as essential to informed public discourse.
Article directly examines what happens when economic data becomes unreliable, implicitly advocating for social and economic order in which institutional information systems function reliably. Unreliable data undermines the institutional framework necessary for rights enforcement and dignity. Content advocates for information integrity as prerequisite for functioning international and social order supporting human rights.
FW Ratio: 50%
Observable Facts
Article examines systemic consequences of unreliable economic data for policy frameworks.
MIT Sloan mission includes advancing 'management practice,' suggesting commitment to improving institutional effectiveness.
Institutional support for research and education in economics, analytics, and management speaks to building human capacity for institution-building.
Inferences
Focus on data reliability speaks to preconditions for functional institutional order capable of supporting human rights.
Institutional commitment to advancing management practice reflects belief that improving institutions serves human development and social order.
Educational mission oriented toward developing 'principled leaders' suggests investment in building ethical institutional capacity.
Article examines implications of unreliable economic data for society and policy. Unreliable data undermines equal treatment under law and informed decision-making affecting all persons. Content implicitly affirms that systemic integrity matters for human dignity.
FW Ratio: 50%
Observable Facts
The article investigates consequences of unreliable economic data at national level.
Content engages with structural economic systems that affect multiple social groups.
Inferences
Examining data reliability in economic systems reflects concern for how institutions treat all persons equitably and transparently.
Analysis of systemic problems suggests implicit commitment to transparency and institutional accountability affecting all.
Article examining economic data reliability touches on participation in cultural and scientific advancement. Economic policy affects research funding, innovation systems, and ability of communities to participate in scientific progress. Accurate data is prerequisite for sound innovation policy.
FW Ratio: 50%
Observable Facts
Article engages with economic systems governing resource allocation and policy affecting research and innovation.
MIT Sloan explicitly advances 'ideas that advance management practice' as part of mission.
Inferences
Focus on data reliability in economic systems reflects concern for informed policy affecting scientific and cultural advancement.
Institutional mission to 'advance management practice' suggests orientation toward improving systems enabling human creativity and innovation.
Content examining reliability of economic data indirectly engages with equal protection before law. Unreliable data undermines equal application of economic policy and legal frameworks that depend on accurate information for fair implementation.
FW Ratio: 50%
Observable Facts
Article investigates systemic consequences of unreliable data affecting policy decisions.
Inferences
Analysis of data reliability speaks to conditions necessary for equal protection—accurate information basis for law and policy application.
Article examining economic data reliability touches on conditions for adequate standard of living and health. Economic policy depends on accurate data; unreliable information leads to poor policy decisions affecting public welfare. Implicit recognition that informed economic governance serves human welfare.
FW Ratio: 57%
Observable Facts
MIT Sloan mission includes developing 'principled, innovative leaders who improve the world.'
Educational programs focus on management, economics, analytics, and business practices affecting societal welfare.
Article published freely in 'Ideas Made to Matter' suggests institutional commitment to disseminating knowledge relevant to public welfare.
Content engages with systemic economic issues affecting policy and collective welfare.
Inferences
Educational mission oriented toward 'improving the world' suggests institutional values aligned with human welfare and dignity.
Focus on data reliability speaks to preconditions for sound economic policy supporting adequate standards of living.
Free publication of economic analysis supports public literacy on issues affecting collective welfare.
The article's framing—examining reliability of economic data and its systemic implications—implicitly engages with Preamble themes of human dignity and social progress. Economic data reliability directly affects policy decisions that impact all persons' fundamental rights and freedoms.
FW Ratio: 60%
Observable Facts
The article title asks 'What happens when US economic data becomes unreliable,' positioning data integrity as consequential to broader systems.
Page byline credits Betsy Vereckey as author and MIT Sloan School as publisher.
Content falls under 'Data' category tag within 'Ideas Made to Matter' publication.
Inferences
The framing suggests that economic data reliability affects collective welfare and institutional decision-making, connecting to Preamble values of social advancement.
Publication by an educational institution implies intent to advance informed understanding of systemic issues relevant to society.
Content examining economic data reliability touches on preconditions for democratic participation. Informed public requires accurate information to participate in governance. Unreliable data undermines ability to make informed electoral and policy decisions.
FW Ratio: 50%
Observable Facts
Article investigates systemic implications of unreliable economic data for policy decisions.
Inferences
Analysis of data integrity as systemic issue implicitly recognizes that accurate information enables informed political participation.
Content does not explicitly address discrimination, but focus on data reliability implies that flawed information can perpetuate or mask discriminatory outcomes in policy. Reliable data is a precondition for identifying and addressing discrimination.
FW Ratio: 50%
Observable Facts
Article examines economic data at systemic level without distinguishing treatment by demographic categories.
Inferences
Discussion of data reliability at aggregate level implicitly acknowledges that distorted information can obscure inequities affecting protected groups.
Content does not explicitly address privacy, but article subject matter (economic data reliability) touches on information systems that can affect privacy. Editorial framing does not prioritize privacy concerns.
FW Ratio: 60%
Observable Facts
Page code contains Google Tag Manager tracking code (GTM-MVBC5PK).
Analytics configuration includes dataLayer and consent mode settings.
No privacy notice or cookie consent banner visible in provided page content.
Inferences
Presence of tracking code without visible consent mechanism suggests routine user data collection aligned with institutional analytics practices rather than privacy-first design.
Tracking infrastructure may collect user behavior data without explicit notice to visitors, raising privacy concerns under Article 12.
No privacy policy or data handling practices observable on page content provided.
Terms of Service
—
No terms of service observable on page content provided.
Identity & Mission
Mission
+0.20
Article 25 Article 26 Article 27 Article 28
MIT Sloan mission statement emphasizes developing 'principled, innovative leaders who improve the world' and advancing 'management practice.' This aspirational framing suggests institutional values aligned with human dignity and collective welfare. Educational mission supports right to education and development of human potential.
Editorial Code
—
No editorial standards or code of conduct observable on page content provided.
Ownership
—
MIT is a private educational institution, accredited and non-profit. No specific ownership conflicts observable.
Access & Distribution
Access Model
-0.10
Article 26
Content appears on an institutional website with no apparent paywall, suggesting open access to educational content. However, underlying educational programs (MBA, PhD, etc.) are selective and tuition-based, limiting practical access to formal education for low-income populations. Modifier reflects partial access for public information dissemination but structural inequity in educational access.
Ad/Tracking
-0.05
Article 12
Page code includes Google Tag Manager (GTM-MVBC5PK) and analytics tracking. Privacy implications for user data collection are not transparent on the provided content. Minimal modifier reflects privacy concern but lack of explicit coercion.
Accessibility
+0.15
Article 2 Article 26
Page includes structured semantic markup (schema.org), alt text for images, skip-to-main-content link, and responsive design patterns, indicating institutional commitment to accessible web design. These structural features support equal access and non-discrimination.
MIT Sloan offers multiple educational pathways (MBA, PhD, Master's programs, Executive Education, Undergraduate) with stated mission to 'develop principled, innovative leaders.' Structural support for education includes faculty expertise (article byline references faculty contributor), research infrastructure, and publication of analysis. Website accessibility and free content dissemination support educational access to broader public beyond enrolled students.
Content published on open, accessible platform without paywall. MIT Sloan disseminates research and analysis freely to public audience. Institutional infrastructure supports publication and distribution of ideas. No observable censorship or restrictions on viewpoint expression. Article available for sharing across social media platforms (LinkedIn, etc.), supporting information circulation.
MIT Sloan operates educational programs aimed at developing leaders who 'improve the world.' Educational infrastructure supports training in economic analysis and management, contributing to human capital development. Accessibility through open publication of research supports broader public understanding relevant to Article 25 (health, welfare, adequate standard of living).
MIT Sloan institutional structure supports research, education, and analysis aimed at improving management and economic systems. Mission to 'generate ideas that advance management practice' reflects commitment to strengthening institutions serving human development. Educational and research infrastructure contributes to building capable institutions able to enforce rights and support social order.
Page code includes Google Tag Manager and analytics tracking, enabling user tracking and data collection. No observable opt-out mechanism or privacy notice on provided content. This structural practice suggests routine collection of user data without explicit consent signals visible on page.
Website operates as a public-facing educational institution portal with global accessibility. No geographic restrictions on viewing educational content observable. Institutional practice supports unrestricted access to information from any location, enabling freedom of information access globally.
Evaluated by claude-haiku-4-5-20251001: +0.39 (Moderate positive) 14,743 tokens
2026-03-15 23:01
rater_validation_warn
Validation warnings for model claude-haiku-4-5-20251001: 19W 20R
--
2026-03-15 22:58
eval_failure
Evaluation failed: Error: Failed to parse slim evaluation JSON: SyntaxError: Expected ',' or '}' after property value in JSON at position 5059 (line 122 column 7). Response starts with: {
"schema_version": "3.7",
"e
--
2026-03-15 22:35
eval_success
PSQ evaluated: g-PSQ=0.120 (3 dims)
--
2026-03-15 22:35
eval
Evaluated by llama-4-scout-wai-psq: +0.12 (Mild positive) 0.00
2026-03-15 21:59
eval_success
Lite evaluated: Mild negative (-0.24)
--
2026-03-15 21:59
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-15 21:59
rater_validation_warn
Lite validation warnings for model llama-4-scout-wai: 1W 1R
--
2026-03-15 18:37
eval_success
PSQ evaluated: g-PSQ=0.120 (3 dims)
--
2026-03-15 18:37
eval
Evaluated by llama-4-scout-wai-psq: +0.12 (Mild positive) 0.00
2026-03-15 18:36
eval_success
Lite evaluated: Mild negative (-0.24)
--
2026-03-15 18:36
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-15 18:36
rater_validation_warn
Lite validation warnings for model llama-4-scout-wai: 1W 1R
--
2026-03-15 17:21
eval_success
PSQ evaluated: g-PSQ=0.120 (3 dims)
--
2026-03-15 17:21
eval
Evaluated by llama-4-scout-wai-psq: +0.12 (Mild positive) 0.00
2026-03-15 17:17
eval_success
Lite evaluated: Mild negative (-0.24)
--
2026-03-15 17:17
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-15 17:17
rater_validation_warn
Lite validation warnings for model llama-4-scout-wai: 1W 1R
--
2026-03-15 16:07
eval_success
PSQ evaluated: g-PSQ=0.120 (3 dims)
--
2026-03-15 16:07
eval
Evaluated by llama-4-scout-wai-psq: +0.12 (Mild positive) 0.00
2026-03-15 16:04
eval_success
Lite evaluated: Mild negative (-0.24)
--
2026-03-15 16:04
rater_validation_warn
Lite validation warnings for model llama-4-scout-wai: 1W 1R
--
2026-03-15 16:04
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-15 15:28
eval_success
PSQ evaluated: g-PSQ=0.120 (3 dims)
--
2026-03-15 15:28
eval
Evaluated by llama-4-scout-wai-psq: +0.12 (Mild positive) 0.00
2026-03-15 15:27
eval_success
Lite evaluated: Mild negative (-0.24)
--
2026-03-15 15:27
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-15 15:27
rater_validation_warn
Lite validation warnings for model llama-4-scout-wai: 1W 1R
--
2026-03-15 14:50
eval_success
Lite evaluated: Mild negative (-0.24)
--
2026-03-15 14:50
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-15 14:49
eval
Evaluated by llama-4-scout-wai-psq: +0.12 (Mild positive) 0.00
2026-03-15 14:14
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-15 14:11
eval
Evaluated by llama-4-scout-wai-psq: +0.12 (Mild positive) 0.00
2026-03-15 13:37
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-15 13:32
eval
Evaluated by llama-4-scout-wai-psq: +0.12 (Mild positive) 0.00
2026-03-15 12:58
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-15 12:51
eval
Evaluated by llama-4-scout-wai-psq: +0.12 (Mild positive) 0.00
2026-03-15 12:19
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-15 12:09
eval
Evaluated by llama-4-scout-wai-psq: +0.12 (Mild positive) -0.16
2026-03-15 11:40
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-15 11:30
eval
Evaluated by llama-4-scout-wai-psq: +0.28 (Mild positive) +0.16
2026-03-15 11:01
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-15 10:46
eval
Evaluated by llama-4-scout-wai-psq: +0.12 (Mild positive) -0.16
2026-03-15 10:22
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-15 10:06
eval
Evaluated by llama-4-scout-wai-psq: +0.28 (Mild positive) +0.16
2026-03-15 09:39
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-15 09:25
eval
Evaluated by llama-4-scout-wai-psq: +0.12 (Mild positive) 0.00
2026-03-15 08:59
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-15 08:42
eval
Evaluated by llama-4-scout-wai-psq: +0.12 (Mild positive) 0.00
2026-03-15 08:19
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-15 08:02
eval
Evaluated by llama-4-scout-wai-psq: +0.12 (Mild positive) 0.00
2026-03-15 07:33
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-15 07:18
eval
Evaluated by llama-4-scout-wai-psq: +0.12 (Mild positive) -0.16
2026-03-15 06:55
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-15 06:39
eval
Evaluated by llama-4-scout-wai-psq: +0.28 (Mild positive) 0.00
2026-03-15 06:20
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-15 06:02
eval
Evaluated by llama-4-scout-wai-psq: +0.28 (Mild positive) +0.16
2026-03-15 05:45
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-15 05:27
eval
Evaluated by llama-4-scout-wai-psq: +0.12 (Mild positive) 0.00
2026-03-15 05:10
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-15 04:52
eval
Evaluated by llama-4-scout-wai-psq: +0.12 (Mild positive) 0.00
2026-03-15 04:35
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-15 04:16
eval
Evaluated by llama-4-scout-wai-psq: +0.12 (Mild positive) 0.00
2026-03-15 03:59
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-15 03:39
eval
Evaluated by llama-4-scout-wai-psq: +0.12 (Mild positive) 0.00
2026-03-15 03:20
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-15 03:00
eval
Evaluated by llama-4-scout-wai-psq: +0.12 (Mild positive) 0.00
2026-03-15 02:45
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-15 02:25
eval
Evaluated by llama-4-scout-wai-psq: +0.12 (Mild positive) 0.00
2026-03-15 02:10
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-15 01:46
eval
Evaluated by llama-4-scout-wai-psq: +0.12 (Mild positive) 0.00
2026-03-15 01:35
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-15 01:15
eval
Evaluated by llama-4-scout-wai-psq: +0.12 (Mild positive) 0.00
2026-03-15 01:09
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-15 00:47
eval
Evaluated by llama-4-scout-wai-psq: +0.12 (Mild positive) 0.00
2026-03-15 00:43
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-15 00:16
eval
Evaluated by llama-3.3-70b-wai-psq: +0.45 (Moderate positive)
2026-03-15 00:12
eval
Evaluated by llama-3.3-70b-wai: -0.24 (Mild negative)
reasoning
Economic data reliability discussion
2026-03-14 23:45
eval
Evaluated by llama-4-scout-wai-psq: +0.12 (Mild positive) 0.00
2026-03-14 23:36
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-14 23:05
eval
Evaluated by llama-4-scout-wai-psq: +0.12 (Mild positive) 0.00
2026-03-14 22:58
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-14 22:03
eval
Evaluated by llama-4-scout-wai-psq: +0.12 (Mild positive) 0.00
2026-03-14 21:57
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-14 21:01
eval
Evaluated by llama-4-scout-wai-psq: +0.12 (Mild positive) 0.00
2026-03-14 20:56
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-14 19:50
eval
Evaluated by llama-4-scout-wai-psq: +0.12 (Mild positive) 0.00
2026-03-14 19:48
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative) 0.00
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri
2026-03-14 18:59
eval
Evaluated by llama-4-scout-wai-psq: +0.12 (Mild positive)
2026-03-14 18:53
eval
Evaluated by llama-4-scout-wai: -0.24 (Mild negative)
reasoning
The article discusses the reliability of US economic data and its implications, but does not explicitly mention human ri