Little agreement why, but men have been dropping out of the US labor force. It has many effects on society, politics and the economy. v Fortune
https://fortune.com/2026/06/21/male-labor-force-participation-rate-decline-childhood-experience-wages-unemployment/

NEW NBER working paper: "'Nobody Wants to Work Anymore': Lifetime Labor Market Experiences and the Decline of Male LFP in the United States"
Remy Levin & Daniela Vidart, University of Connecticut
https://www.nber.org/papers/w35327
#economics #LaborEconomics

Why men keep dropping out of the labor force: It starts in childhood, when kids see how males around them struggle, economists say

"Our findings suggest that experience effects can turn short-run declines in labor demand into long-run declines in labor supply."

Fortune

ROCKWOOL Foundation Berlin – Institute for the Economy and the Future of Work (RFBerlin) is looking for a research assistant to build data on academics and patents and design AI agents that do the real work. Paid, flexible, Berlin.

RFBerlin is an independent research institute. We conduct research into significant and global challenges to the economy, society and the welfare state.
Apply by 5 July:
https://www.rfberlin.com/job/student-assistant-waldinger-schwarz/
#EconJob #LaborEconomics #AppliedMicro #GetFediHired

Student Research Assistant

We at RFBerlin we are looking to employ one or two Bachelor's students as research assistants. The position involves at least 10 hours per week at an hourly rate starting from €13,19. Working hours are flexible. The Project The project investigates how political institutions shape scie

RFBerlin

The Myth of Meritocracy

By Cliff Potts, CSO, and Editor-in-Chief of WPS News

Baybay City, Leyte, Philippines — Thursday, June 4, 2026, 8:30 a.m. Eastern Time

Meritocracy is widely assumed to be the organizing principle behind modern hiring and governance. The idea is simple and reassuring: the most capable individuals rise to positions of responsibility based on skill, effort, and demonstrated competence. Yet observable outcomes increasingly contradict this assumption. Repeated leadership failures, institutional stagnation, and persistent misalignment between authority and capability suggest that meritocracy, as commonly understood, is not functioning as advertised.

This article examines what merit-based selection would actually require, how current systems operate instead, and why the gap between the two matters for institutional survival.

What Merit-Based Selection Would Require

In practical terms, a merit-based system would prioritize demonstrated ability to perform the work in question. That includes relevant skills, judgment under uncertainty, the capacity to synthesize information across domains, and a documented record of making sound decisions over time. It would also require the ability to challenge faulty assumptions and adapt when conditions change.

Merit-based selection is not about perfection or elite credentials. It is about functional competence: whether an individual can reliably perform the duties of the role in real-world conditions. In complex organizations, this often includes experience navigating failure, recognizing systemic risk, and correcting course without external prompting.

If such criteria were consistently applied, outcomes would show a strong correlation between authority and performance. In many institutions, they do not.

What Current Systems Actually Measure

Modern hiring systems rarely evaluate candidates on their ability to do the work as it is actually performed. Instead, they prioritize signals that can be quickly processed at scale. These include resume formatting, keyword alignment with job descriptions, credential familiarity, and narrative conformity.

The widespread use of automated screening tools has intensified this shift. Resumes are increasingly filtered based on textual similarity rather than substantive capability. Candidates who are adept at mirroring job descriptions, regardless of whether they possess the underlying skills, are rewarded with visibility. Those whose experience does not translate cleanly into standardized language are often excluded early in the process.

This approach favors candidates who understand how to perform alignment rather than those who understand how to perform the work. Over time, this creates a selection bias toward presentation skill and institutional legibility, rather than competence.

Automation and the Scaling of Bias

Hiring platforms did not invent these biases, but they have amplified them. Systems designed to manage large applicant pools rely on reduction: fewer variables, simpler comparisons, and faster elimination. As a result, nonconforming candidates are filtered out not because they are unqualified, but because they are difficult to categorize.

Automation rewards predictability. It penalizes unconventional career paths, cross-disciplinary experience, and non-linear progression—traits that are often associated with problem-solving and innovation. The more an applicant resembles a predefined template, the more likely they are to advance.

This dynamic creates a paradox. As organizations claim to seek innovation and adaptability, their selection systems increasingly favor sameness and risk avoidance.

Observable Outcomes That Contradict Meritocracy

If meritocracy were operating effectively, leadership outcomes would improve over time. Institutions would learn from past failures, retain institutional memory, and demonstrate increasing competence in crisis management. In many cases, the opposite is true.

Across sectors, organizations repeatedly elevate individuals who perform well in stable conditions but struggle under stress. Decision-makers are recycled despite documented failures. Strategic errors are repeated even when prior consequences are well known. Responsibility is diffuse, while accountability is limited.

These patterns are not random. They are consistent with selection systems that prioritize safety, familiarity, and non-disruption over demonstrated ability.

Risk Avoidance as a Selection Principle

One of the least examined drivers of modern hiring is risk avoidance. Selection processes are often structured to minimize perceived downside rather than maximize potential upside. Candidates who might challenge existing assumptions, expose internal weaknesses, or disrupt established hierarchies are treated as liabilities.

This approach is reinforced by legal and reputational pressures. Subjective judgments are embedded in language such as “culture fit,” “communication style,” or “organizational alignment.” These criteria are difficult to measure, difficult to contest, and easy to defend after the fact. They also allow decision-makers to exclude candidates who are competent but inconvenient.

Over time, risk avoidance becomes self-reinforcing. Institutions staffed by individuals selected for minimal disruption become less capable of recognizing or responding to systemic threats.

Why the Meritocracy Myth Persists

Despite mounting evidence, the belief in meritocracy remains deeply entrenched. One reason is that it provides moral cover. If outcomes are assumed to be merit-based, failures can be attributed to individual shortcomings rather than systemic design. This deflects scrutiny from selection mechanisms themselves.

Another reason is that the myth benefits those already in positions of authority. If the system is presumed fair, existing hierarchies appear justified. Questioning the validity of merit-based selection challenges not only hiring practices, but the legitimacy of current leadership.

As a result, institutions often invest more effort in defending the appearance of meritocracy than in examining whether it functions in practice.

Why This Matters Beyond Hiring

Selection systems shape more than careers. They shape institutional intelligence. When organizations consistently choose candidates based on legibility and conformity rather than capability, they reduce their capacity to learn, adapt, and respond to change.

In periods of stability, these weaknesses may remain hidden. In periods of disruption, they become visible quickly. The consequences include delayed responses, misallocation of resources, and an inability to correct course before failures become systemic.

Meritocracy is often framed as a moral ideal. In reality, it is a functional requirement. Institutions that fail to align authority with competence do not merely become unfair. They become fragile.

This article begins a series examining how modern hiring and governance systems have drifted away from merit-based selection, what has replaced it, and why that shift is undermining institutional performance. Subsequent articles will document the specific mechanisms that now govern access to decision-making authority, and the costs of maintaining them.

For more social commentary, please see Occupy 2.5 at https://Occupy25.com

References

Berg, J. M., Grant, A. M., & Johnson, V. (2010). When callings are calling: Crafting work and leisure in pursuit of unanswered occupational callings. Organization Science, 21(5), 973–994. https://doi.org/10.1287/orsc.1090.0497

Cappelli, P. (2019). Your approach to hiring is all wrong. Harvard Business Review Press.

Highhouse, S., Brooks, M. E., & Gregarus, G. (2009). An organizational impression management perspective on the formation of corporate reputations. Journal of Management, 35(6), 1481–1493. https://doi.org/10.1177/0149206309348788

Rivera, L. A. (2012). Hiring as cultural matching: The case of elite professional service firms. American Sociological Review, 77(6), 999–1022. https://doi.org/10.1177/0003122412463213

Autor, D., Levy, F., & Murnane, R. J. (2003). The skill content of recent technological change: An empirical exploration. Quarterly Journal of Economics, 118(4), 1279–1333. https://doi.org/10.1162/003355303322552801

#credentialism #eliteHiring #governanceAnalysis #hiringPractices #institutionalFailure #laborEconomics #meritocracy #organizationalRisk #workforceSystems

In 1961, a robot took a job no one wanted. The same robot would have been helpless in a kitchen. Danger isn't a property of an environment. It's a relationship between an environment and the body encountering it. New post on the ecology of work and what robots taught us about human fitness:
https://jameshoward.us/2026/05/29/the-ecology-of-work/

#AI #Robotics #LaborEconomics #AIHistory

The Ecology of Work

Nobody wanted the job. That is the detail that gets lost in every retelling of what happened at General Motors’ Inland Fisher Guide Plant in Ewing Township, New Jersey, in...

James Howard
📈📉 Standard Error is delighted to announce that Sarah Winton (LSE ’26) has been awarded the Best Paper Prize at the 7th Workshop on the Economics and Politics of Migration. 🧵 1/9 stderr-editors.com/blog/best-pa... #Migration #Refugees #LaborEconomics #DevelopmentEconomics

Standard Error awards Best Pap...
Standard Error awards Best Paper Prize at Rome migration research workshop to Sarah Winton

The research finds that Jordan's 2016 policy granting Syrian refugees work authorization increased overall output by 10.9% and raised Jordanians' average wages by nearly 1%.

Standard Error

Every job eliminated and attributed to AI resets market expectations for that function, like a house selling at a loss that resets comps for the whole street. The workers who remain negotiate against a smaller market with fewer openings, and their bargaining power drops whether or not AI is actually doing the work.

https://readuncut.com/the-ai-bet-corporate-america-actually-made-it-wasnt-productivity/

#WageSuppression #LaborEconomics #AIImpact #Negotiation #MarketDynamics

AI Layoffs and Wage Compression: The Bet Corporate America Made

AI gave corporate America a way to gut headcount and get applauded for it. An NBER study found only 2% of execs attributed cuts to actual AI, but 60% cut in anticipation of efficiencies that haven't arrived. The bet was never productivity. It was permanent wage compression with better PR.

Read Uncut

Fear and Loathing of AI (Part III): “Learn AI” Is the New “Learn to Code”

By Cliff Potts, CSO, and Editor-in-Chief of WPS News

There is a sentence that shows up in every technological cycle right before the disappointment phase begins.

“Just learn the skill.”

It sounds empowering. It sounds reasonable. It sounds like personal agency.

It is also a lie we have been telling people for decades.

The obedience script

“Learn to code” was never about opportunity.
It was about discipline.

It trained people to accept that:

  • structural failures are personal problems,
  • economic insecurity is an individual moral test,
  • and survival depends on constant retraining at your own expense.

When the promised jobs didn’t materialize—or paid far less than advertised—the story shifted seamlessly: you didn’t learn the right language, the right framework, the right stack.

Now the phrase has been updated.

“Learn AI.”

Same script. Same pressure. Same outcome.

Skills don’t collapse — markets do

Coding did not fail because people were lazy or incapable. It failed because markets flooded, tools commoditized, and labor lost leverage.

AI will follow the same arc, only faster.

The moment a skill becomes:

  • widely accessible,
  • easily automated,
  • and expected rather than rewarded,

it stops being a path to security and becomes a baseline requirement for staying afloat.

The reward for compliance is not prosperity.
It is continued participation.

Training as cost transfer

Here is what “learn AI” really means in practice:

  • You pay for the courses.
  • You absorb the time cost.
  • You shoulder the career risk.
  • You adapt repeatedly as tools change.
  • You accept lower pay because “AI makes you more efficient.”

None of that is accidental.

It is a system designed to push costs downward while extracting value upward.

The more often you are told to retrain, the clearer it becomes that training itself is the product.

The illusion of agency

People are encouraged to believe that mastery equals control.

But control does not come from skill alone.
It comes from:

  • ownership,
  • bargaining power,
  • regulation,
  • and collective leverage.

Without those, skill is just labor dressed up as self-improvement.

Learning AI may help you keep your job a little longer.
It will not protect you from the logic of the system deploying it.

What learning actually means now

This does not mean you should refuse to learn.

It means you should learn without illusions.

Learn AI the way you learn any tool:

  • to reduce friction,
  • to save time,
  • to extend what you already do.

Do not learn it expecting salvation.
Do not learn it expecting loyalty from platforms.
Do not learn it expecting the market to reward you for effort.

Markets reward leverage, not diligence.

The quiet truth

The most dangerous part of “learn AI” is not that it is false.

It is that it is incomplete.

It tells people how to adapt, but never who benefits.
It demands flexibility, but never offers stability.
It promises relevance, but never guarantees dignity.

We have seen this cycle before.

And it did not end with freedom.

It ended with exhaustion.

For more social commentary, please see Occupy 2.5 at https://Occupy25.com

#AISkills #ArtificialIntelligence #economicPrecarity #futureOfWork #laborEconomics #learnToCode #Occupy25 #platformCapitalism #technologyHype #workforceRetraining #WPSNews

Labor is the most expensive thing a company buys, more expensive than the cloud infrastructure, more expensive than the office space, more expensive than the espresso machine nobody asked for but the CFO approved because morale was circling the drain and a Breville seemed cheaper than addressing why. https://readuncut.com/the-ai-bet-corporate-america-actually-made-it-wasnt-productivity/

#AI #LaborEconomics #CorporateAmerica #TechLayoffs

AI Layoffs and Wage Compression: The Bet Corporate America Made

AI gave corporate America a way to gut headcount and get applauded for it. An NBER study found only 2% of execs attributed cuts to actual AI, but 60% cut in anticipation of efficiencies that haven't arrived. The bet was never productivity. It was permanent wage compression with better PR.

Read Uncut

TVs get cheaper every year. So does fast fashion. But rent, healthcare, and college tuition keep climbing. Baumol explained this in 1966. We're still living it. by @daylightatheism.bsky.social

https://onlys.ky/cost-disease/

#Economics #CostOfLiving #Inequality #LaborEconomics #PublicPolicy

Cost disease: Why everything is so damn expensive

There's a deeper cause than greed or inefficiency.

OnlySky
Choice Architecture in Occupational Choices
http://repec.business.uzh.ch/RePEc/iso/leadinghouse/0255_lhwpaper.pdf
This study uses a Swiss job board to analyze how rank order and design influence high-stakes occupational choices. Higher rankings increased applications, especially for high-paying and gender-congruent occupations. Users interpreted rank to justify choices aligning with identity, providing field evidence for motivated reasoning. An interactive, visually enriched interface redesign boosted applications and watch list usage. Results show that reducing cognitive load expands the variety of options individuals consider and remember.
#choicearchitecture #motivatedreasoning #laborEconomics #jobtech #ExperimentalEcon
#BoundedRationality