Unions These Days – Recent Events, and What Their Presence Indicates

Trade unions have a long world history, mostly but hardly exclusively beneficial.  Now it is 2025, and few alive can even remember the pre-union times when, for example, if American workers died on the job they would not even get that day’s pay.  Labor laws, assuring physical and legal employee protections are extensive, widespread, noncontroversial and effective, and few companies run afoul of them.  So where do unions come in now?

First, a few of the large, related stories from the past nine months.

In “The Delivery Business Shows Why Unions Are Struggling to Expand” (The New York Times, May 27^th), Peter Eavis contrasted worker-organization victories, as those “representing workers at three large automakers and UPS negotiated new labor contracts that included big raises and other gains,” with “labor experts” saying “structural forces would make it hard for labor groups to increase their membership.”  One of those is the large share of workers not being employees of the companies at whose locations they report.  Others are increasing part-time work, high turnover in fields otherwise ripe for organizing, and frequent requirements that unions start simultaneously at all of an employer’s often-far-flung locations.  Still, unions have done some amazing things, exemplified by the statistic that the “average annual compensation, including benefits” of UPS drivers is now $170,000. 

Moving to efforts at another huge, well-known company, Matt Bruenig wrote in the August 21^st New York Times that he saw “In a Union Triumph, the Seeds of Future Failure.”  Starbucks employees, he noted, “have unionized 481 stores with more than 11,000 employees in less than three years,” which has, though, also revealed that “American labor laws, and the bureaucracy they require, make mass unionization impossible unless rules for certifying unions and negotiating contracts are simplified and streamlined.”  The National Labor Relations Board, responsible for holding many union elections as well as dealing with worker complaints, has been overtaxed.  “Anti-union activity by employers” is still a problem, and it is not even the law that union authorization requires only most workers signing certification cards.  While bills with legislation ending these concerns have been written and presented, they not been successfully voted in – and seem unlikely to be over the next several years.

The situation at the coffee seller reached a head four months later, as “Starbucks Baristas Walk Out in 3 Cities” (Heather Haddon, The Wall Street Journal, December 21^st -22^nd, 2024).  They were Chicago, Los Angeles, and Seattle, and the picketing, “walkouts,” and “protests” were over five days later, without agreement on a contract.  Later, we saw “Starbucks and Union Agree to Mediation in Quest for Contract” (Danielle Kaye and Rebecca Davis O’Brien, The New York Times, January 30^th), as the company, which “called the union’s wage proposals “not sustainable,”” “did not offer a substantial wage increase during the latest bargaining session in December.” Starbucks’ management has choices to make, on which they will be forced if they do not resolve them freely.

Also last month, and with a group of employees rather better compensated than baristas, there was a “Port Strike Averted With Labor Deal Days Before Deadline” (Peter Eavis, The New York Times, January 8^th).  The dockworkers’ union, the International Longshoremen’s Association, and the United States Maritime Alliance representing employers, “overcame their differences over a big sticking point in their talks:  the introduction of automated cargo-moving machinery at the ports.”  The resolution cemented an agreement on wages to go up over 60% during the time between now and 2031, and calls for positions to “be added when automated equipment was added at a port,” which will give hirers “a more straightforward path for introducing automated machinery.”  By the end of the six years, dockworkers will be getting $63 per hour, and “with shift work and overtime, the pay of many longshoremen at some East Coast ports could rise to well over $200,000 a year.” 

With container ship commerce vital nationally, the International Longshoremen’s Association is in an exceptionally strong bargaining position.  But that is not the case for unions at Starbucks or Amazon.  They are new, and the reason for their ascent is clear: their constituents have legitimate gripes.  That’s what emerging unions need now.  With truly inhumane treatment of employees almost completely a thing of the past, it is time for companies to take fresh union activity as a wake-up call.  What are they doing wrong?  It’s something.  They need to be aware of that before the organizing starts.  If they do, it won’t happen.  If they don’t, and end up in Starbucks’ position of needing to pay more than they think their businesses can take, they have only themselves to blame.

Artificial Intelligence Progress, Problems, and Perceptions: Two Months’ Worth

Recently, the DeepSeek kerfuffle has dominated the AI news.  But since late December, other things beyond future-success assertions have hit the news.  What are they?

First, “OpenAI Unveils New A.I. That Can ‘Reason’ Through Math and Science Problems” (Cade Metz, The New York Times, December 20^th).  Its new product, o3, now in the hands of “safety and security testers, outperformed the industry’s leading A.I. technologies on standardized benchmark tests that rate skills in math, science, coding and logic,” being over 20% more accurate than its predecessor “in a series of common programming tasks.”  That area has received less publicity, but AI has been serving more and more in human programmers’ core roles.  Yet, per OpenAI CEO Sam Altman, “at least one OpenAI programmer could still beat the system on this test,” meaning AI has not taken over superiority yet, and it “can still get things wrong or hallucinate.”  But we’ve seen a big improvement here.

The upcoming main OpenAI system, though, does not look as good, as “The Next Great Leap in AI Is Behind Schedule and Crazy Expensive” (The Wall Street Journal, December 21^st).  Author Deepa Seetharaman said about GPT-5, code named Orion, that “it isn’t clear when – or if – it’ll work,” as “there may not be enough data in the world to make it smart enough.”  This product, intended to succeed GPT-4 and its variants, is being developed with what could soon be regarded as the old way of building AI, with ever-more-gigantic datasets and similarly huge amounts of electricity and processing power, in this case costing “around half a billion dollars in computing costs alone.”  It’s now almost two years in the making, and still does not have even a traditionally overoptimistic release date.

Moving to an application, we saw “Platonic Romances and A.I. Clones: 2025 Dating Predictions” (Gina Cherelus, The New York Times, January 3^rd).  The author predicted less conventional dating and less use of conventional dating applications.  AI may become “your ultimate wingman” as it may be more frequently used to “write… profiles, edit photos and write entire dialogues… on dating apps,” and “some will even use A.I. clones to do the whole thing for them” as people have done with structurally-similar job applications.  As well, people may “use A.I. dating coaches to practice chats before a date, help them come up with conversation topics and suggest preplanned date ideas in their cities.”  At that point, AI had better be able to produce unique output streams, since it wouldn’t be much fun to be able to anticipate what a prospective romantic partner is next going to say, word-for-word.

Among our president’s immediate proclamations was “Trump announces largest AI infrastructure project ‘in history’ involving Softbank, OpenAI and Oracle” (Brock Dumas, Fox Business, January 21^st).  Despite those company’s CEOs joining “Trump from the Roosevelt Room at the White House for the announcement,” there is doubt whether they will meet the cost of “$100 billion, with plans to expand to $500 billion over the next four years” – and if they do, the project may serve only as a framework for capital expenditures they were planning to make anyway.

Another jump in actually-available AI capability occurred with “OpenAI launches Operator – an agent that can use a computer for you” (Will Douglas, MIT Technology Review, January 23^rd).  The software “can carry out simple online tasks in a browser, such as booking concert tickets or filling an online grocery order.”  There are already similar tools at Anthropic (Claude 3.5 Sonnet) and Google DeepMind (Mariner).  This one may be a cause for security worry, as there are plenty of ways of initiating physical action from a keyboard, so these apps will need to be constrained somehow.

“When A.I. Passes This Test, Look Out” (Kevin Roose, The New York Times, January 23^rd).  It has been produced by the Center for AI Safety and Scale AI, and it is called “”Humanity’s Last Exam.””  It has “roughly 3,000 multiple-choice and short answer questions designed to test A.I. systems’ abilities in areas ranging from analytic philosophy to rocket engineering,” which are “”along the upper range of what one might see in a graduate exam.””  If researchers can sufficiently restrict sharing these questions and their answers, this exam might last a while without AI solution, or it could topple within a year or two.

 A new look at an old subject, “Is Artificial Intelligence Really Worth the Hype?” was written by Jeff Sommer and published February 7^th in the New York Times.  Its main cause for concern was about DeepSeek, and, as of this date, investors were “re-evaluating prominent companies swept up in A.I. fever, including Nvidia, Meta, Alphabet, Microsoft, Amazon, Tesla and the private start-up OpenAI.”  In the week since this piece came out, there have been serious concerns voiced about the legitimacy and credibility of DeepSeek’s claim, and, since there is no other focus of unease in this article, we can’t accept it yet.  There are still plentiful reasons to think AI will not even approximate its highest expectations, and there will be more stories with similar titles, but the DeepSeek controversy – and that’s what it is – has not been resolved yet.  Neither has a clear vision of what AI will be doing, and not doing, even a few years from now.  We’ll see – that’s all.

A Just-Good Employment Report, with AJSN Showing Latent Demand for 17.1 Million Jobs

This morning’s Bureau of Labor Statistics Employment Situation Summary was to have two features: Estimated new nonfarm payroll positions up from 170,000 to 175,000, and many annual data adjustments muddying comparisons with December and other recent months. 

We got the second, but not quite the first.  Jobs as above missed the mark with 143,000.  However, almost all the other results were favorable.  Seasonally adjusted unemployment ticked down 0.1% to 4.0%, with the unadjusted variety up seasonally from 3.8% to 4.4%.  The adjusted number of unemployed lost 100,000 to 6.8 million, with the count of long-term jobless, looking for 27 weeks or longer, down 200,000, on top of last month’s 100,000 improvement, to 1.4 million.  The two best measures of closeness to working, the labor force participation rate and the employment-population ratio, each added 0.1% to reach 62.6% and 60.1%.  Those employed part-time for economic reasons, or keeping such jobs while thus far unsuccessfully looking for full-time ones, gained 100,000 to 4.5 million.  Average hourly private nonfarm payroll wages rose 18 cents, or more than double recent inflation, reaching $35.87. 

The American Job Shortage Number or AJSN, the metric showing how many additional positions could be quickly filled if all knew they would be easy to get, was up 900,000, mostly seasonally, as follows:

The largest change from last month was from official unemployment, as the AJSN is not seasonally adjusted, which added almost exactly the amount that it increased overall.  There were gains from those wanting work but discouraged, like-thinking people not searching for it in the past year, and those only temporarily unavailable.  All of these were more than offset by the count of those in the armed services, in institutions, and off the grid catching up with last time’s jump in the Census Bureau population estimate, as that component reflects the difference between American population aged 15 and over and those in all other categories.  The share of the AJSN from those officially unemployed was 39.3%, 3.4% higher than in December.

Compared with a year before, the AJSN was almost unchanged, with higher contributions from those unemployed, discouraged, and not wanting work cancelled by fewer not searching for a year or more and a large decrease in the assessed number of American expatriates.

How did the adjustments affect this week’s data?  Befitting the change in population with which they had previously been synchronized, almost everything grew.  The employment numbers and percentages changed in inconsistent ways from the previous month, but still seem to have improved.  I don’t know if, with the stated counts of those not in the labor force increasing by about 1 million and 800,000 more not interested, that many people gave up on job searches, but, clearly, many did.  So once again we need to factor down the positive outcomes, which brings the report down from excellent to just positive.  On that, the turtle took a step forward, but only a moderate one.

The DeepSeek Artificial Intelligence Breakthrough: What Is Really Going On?

This week’s AI news item was the most powerful from that surging field in years.  What on earth happened?

The same day the story broke came out “What to Know About DeepSeek and How It Is Upending A.I.” (Cade Metz, The New York Times, January 27^th).  Immediately, “tech stocks tumbled.  Giant companies like Meta and Nvidia faced a barrage of questions about their future.  Tech executives took to social media to proclaim their fears.  And it was all because of a little-known Chinese artificial intelligence start-up called DeepSeek.”  Word spread that that company had “created a very powerful A.I. model with far less money than many A.I. experts thought possible.”  Veteran technology reporter Metz posed and answered ten questions.  “What is DeepSeek?... A start-up founded and owned by the Chinese stock trading firm High-Flyer,” which “by 2021… had acquired thousands of computer chips from the U.S. chipmaker Nvidia,” and “on Jan. 10… released its first free chatbot app.”  “Why did the stock market react to it now?”  Because DeepSeek released a research paper claiming that while “the world’s top companies typically train their chatbots with supercomputers that use as many as 16,000 chips or more,” its own “engineers said they needed only about 2,000.”  “Why is that important?”  Cost.  “How did DeepSeek make its tech with fewer A.I. chips?”  By “spreading… data analysis across several specialized A.I. models” instead of doing it all together.  “Is DeepSeek’s tech as good as systems from OpenAI and Google?”  Yes, according to “standard benchmark tests.”  “U.S. tech giants are building data centers with specialized A.I. chips.  Does this still matter, given what DeepSeek has done?”  Yes, the additional chips will still be useful for future and peripheral AI purposes.  “Hasn’t the United States limited the number of Nvidia chips sold to China?”  Yes, and that has “forced researchers in China to get creative.”  “Does DeepSeek’s tech mean that China is now ahead of the United States in A.I.?”  No, not in general.

The next day, but probably only hours later, saw “DeepSeek’s Rise:  How a Chinese Start-Up Went From Stock Trader to A.I. Star” (Meaghan Tobin, Paul Mozur, and Alexandra Stevenson, The New York Times).  It was “a business using A.I. to make bets in the Chinese stock market” that “pursued a new opportunity” and “zeroed in on research” on “advanced A.I.”  “Do China’s A.I. Advances Mean U.S. Technology Controls Have Failed?” (Ana Swanson and Meaghan Tobin, The New York Times, January 28^th)?  No, because such limitations had not yet gone into effect when DeepSeek bought their chips.  In contrast, “DeepSeek will not be able to legally purchase the newest generation of A.I. chips that Nvidia is rolling out right now.” 

We got two opposite views on where these stocks are going.  Per Adria Cimino in The Motley Fool on January 28^th, “Nvidia predicted to soar in 2025 thanks to this one thing.”  That reason is innovation, as it may release two new architecture systems before this year is out.  Alternatively, in “I Study Financial Markets.  The Nvidia Rout Is Only the Start,” in the New York Times that day, Mihir A. Desai claimed that “Big Tech is eating itself alive with its component companies throwing more and more cash at investments in one another that are most likely to generate less and less of a return,” and “investors see these companies as a safe bet and have thus stopped demanding significant immediate returns,” resulting in a “massive influx of cheap money.”

What’s going on here?  I have three thoughts that may help us understand.

First, the runup of Nvidia, and other AI stocks to a lesser extent, has long been paper-thin.  Despite all the money involved, only a few people in moderate-sized companies can have huge and sudden impacts.

Second, training AI systems, as well as how AI decides what to say, is a black box.  Even top researchers fail to comprehend exactly how it works, and therefore what it requires.  It is hardly a mature science.

Third, despite the appearance of transparency provided by such things as formal papers, the Chinese government and Chinese society are closed.  We cannot verify, for example, the provenance and originality of DeepSeek’s output, or how much in resources its development actually required.  If the announcement caused $1 trillion in paper assets to disappear, it could be that $500 billion, or more, was due to exaggeration or downright fraud.  Although the amounts of money are unprecedented, this would not be the first time – or the 20^th – that the stock market has been shaken by faulty information.  The technicians at the AI companies will scrutinize DeepSeek’s products and will draw conclusions, but they will not be finished today or tomorrow.  In the meantime, the rest of us need to look before leaping.

The First Batch of Trump’s Executive Orders: How Good Will They Be for Jobs and the Economy?

After his inauguration, President Donald Trump let little grass grow under his feet.  Soon enough to make inclusion in “Tracking Trump’s executive orders:  What he’s signed so far” (Avery Lotz, Axios.com), released around 9am Eastern Time on Wednesday or 45 hours into his presidency, he had released 29 of them.  The two seeking to end birthright citizenship, ensconced in our Constitution, were stillborn, and in fact were blocked by a judge yesterday. 

Otherwise, what effect will his acts have on our employment and prosperity? 

In assessing their probable effects, I took “jobs” to mean the number of full-time positions for all wanting them, regardless of pay.  For “the economy” I figured their probable impact on a family near the 50^th percentile of American affluence, perhaps a family of four with $70,000 annual household income and an ordinary house or apartment, and access to reasonable lifestyle choices.  I judged the remaining 27 orders either positive, neutral, or negative on both, without attempting to assess the degree, so each would end up with two scores, +1, 0, or -1 on employment and the same on prosperity.  Here are the values I assigned, within the nine groups Lotz put them into.

There were four in the “immigration” section.  To Trump’s naming ““certain international cartels” and organizations” as terrorist, I assigned no effect on jobs or the economy.  On suspending refugee resettlements I gave a plus on jobs, since more would stay available, but a minus on the economy, as it would lose relatively low-paid workers.  For similar reasons I attributed the same to the flights canceled for those from Afghanistan, and to the end of “parole programs.”  Overall, this section ended at +3 for jobs and -3 for the economy. 

The two orders Trump issued under the “Remain in Mexico” heading, canceling border crossing appointments and empowering “officials to “repeal, repatriate or remove any alien engaged in the invasion” of the southern border,” drew my same assessment, making the section total +2 for jobs and -2 for the economy, for a running total of +5 and -5.

The next, “energy and environment,” broke the pattern.  I considered freeing up Alaska coastal areas for energy production positive for both jobs and the economy.  For mirror-image reasons, though, his stopping “approvals, rights of way, permits, leases, or loans for onshore or offshore wind projects” would be negative for both, meaning no net effect here, with the overall totals of +5 and -5 staying the same.

Trump had three executive orders pertaining to climate-related policies.  Withdrawing from the Paris Climate broke even.  Allowing “application reviews for liquefied natural gas export projects, which were paused” precipitated a gain for jobs but no change for prosperity.  His revoking “a 2021 Biden executive order that set a goal for 50% of US vehicle sales to be electric by 2030,” meaning that liquid fuel vehicles would replace some future ones, had no net effect.  Overall, this section added +1 for jobs and no change to the economy, getting us to +6 and -5.

Five of the executive orders were “targeting DEI and transgender Americans.”  None of the five had any effect on employment.  Since prosperity is not only what tangible things people can get but the range of other choices they have and can implement, I assigned detractions for his proclamation that “sexes are not changeable and are grounded in fundamental and incontrovertible reality” and his eliminating policies that “widened sex discrimination protections to include sexual orientation and gender identity.”  Those were offset by prosperity improvements, to my way of thinking, from ordering the Federal Aviation Administration “”to immediately return to non-discriminatory, merit-based hiring,”” and the “compliance investigations of publicly traded corporations” among others.  With the executive order moving toward banning transsexuals in the military having no required action and therefore no impact, the section did the same:  jobs still +6 so far, the economy still -5.

Two more were in the “other executive orders affecting federal workers.”  The first, mandating “a full-time return to in-office work for federal employees” and instituting “a hiring freeze on government positions,” got a minus for jobs on the second part and nothing on the first.  The other, “which could make it easier to fire civil servants deemed disloyal,” caused a drop in prosperity and no change to jobs.  That makes this section minus 1 for each, bringing us to +5 and -6.

There were also two in the “health executive orders” group.  Leaving the World Health Organization meant a cut in prosperity, with no effect on employment.  Rescinding “a 2022 Biden order to lower the cost of prescription drugs” I evaluated as the same.  The running totals here stand at +5 and -8.

The final category, covering “TikTok extension, DOGE and more executive orders,” included seven more.  “Ensuring government agencies do not “unconstitutionally abridge the free speech of any American citizen”” was worth a gain only to prosperity.  “Ordering a review of trade practices and agreements,” and revoking various security clearances, had no effect on either.  “Formally establishing the Department of Government Efficiency,” which could turn out to be the best Trump change, was worth increases in both jobs and the economy.  The remaining three, “suspending the TikTok ban for 75 days,” saying that “federal buildings should “respect regional, traditional, and classical architectural heritage”” and the silly “renaming,” if people actually follow that, of Denali and the Gulf of Mexico, had no effects.  That brings the final total up to a gain of 6 for jobs, and a loss of 6 to the economy.

Is declining prosperity at the expense of jobs, as strange as that sounds, what we can expect from Trump’s current term?  Probably it is.  The issue on which he campaigned, and with which he may be most closely associated, tariffs, would also clearly help the number of American jobs but hurt American prosperity, as people not employed in those areas will be paying more.  Although we do not know whether these orders will be sustained, their general, overall direction is clear.  That will probably be matched by Trump’s legislative initiatives. 

Accordingly, we will probably be looking at lower unemployment but higher prices.  That combination means, disappointingly to many, that interest rates should not go down; if they do, we would be risking both a superheated jobs market and even more resurgent inflation.  So, although Trump has been wishing for lower interest rates, it will be his policies that prevent that.  Such is ironic – but many other things about the next four years will also be.

Four Corporate Practices That May Surprise You – And Displease You

What have those pesky managers at our largest companies have been up to?

In “Is Your Driving Being Secretly Scored?” (The New York Times, June 9^th), author Kashmir Hill asked “You know you have a credit score.  Did you know that you might also have a driving score?”  That, also called “telematics,” which “reflects the safety of your driving habits – how often you slam on the brakes, speed, look at your phone or drive late at night,” is supplied to insurance companies from car manufacturers, or “from apps that drivers already have on their phones,” which can include Life360, MyRadar, and GasBuddy.  These tools often have their extra capabilities explained in legal-looking fine print, often unspecifically, such as “we may collect third party data and reports.”  Yet auto insurers have long used personal data, so this is nothing totally new.  In most cases, it can be shut down, or you can choose to do as I did – leave it alone knowing that relaying boring driving habits can only reduce your premiums.  Those more privacy-concerned can dig out this article for much more – it printed to 11 pages.

Another thing I hadn’t seen before, with its absence glaringly obvious, was from Erica Lamberg in Fox Business on July 16^th: “Hot career trend ‘hushed hybrid’ has managers choosing the employees who have flex work arrangements.”  Back in the day, and since then as far as I can see, employers did not seem to care about productivity or responsible behavior when deciding whether to allow workers to stay at home, but, despite official policies banning that, here we have, secretly, better employees being given some privileges.  “Hushed hybrid” can be defined as “managers overruling, dismissing or choosing not to enforce a company’s return-to-office policies.”  Although it is high time that firms used individual assessments, formal or not, to decide who can work remotely, the problem is that those not chosen may feel deceived about the true policy.  It would be better if management could do this openly – if there are no unions involved, it seems like they should be able to.

A few years ago we got publicity about different customers being charged different prices, even when all aspects of the transactions involved were identical or nearly so.  It may be expanding with new developments, as “FTC probes AI-powered ‘surveillance pricing’ at Mastercard, JPMorgan Chase, McKinsey and others” (Eric Revell, Fox Business, July 23^rd).  The new method uses “AI and other technology” combined with “personal information… such as their location, demographics, credit history, and browsing or shopping history” “to analyze consumer data to help set price targets for products and services.”  The Federal Trade Commission, along with masses of people buying things, did not like that, and it may be banned.

Workers’ long-time frenemy found the spotlight in “So, Human Resources Is Making You Miserable?” (David Segal, The New York Times, August 3^rd).  HR, which “bugs a lot of employees and managers… seems to have more detractors than ever since the pandemic began,” when it “began to administer rules about remote work and pay transparency, programs to improve diversity, equity and inclusion and everything else that has rattled and changed the workplace in the last four years.”  Those in that department are themselves “aggravated or bummed out,” often because “office behavior post-Covid has become notably less civil,” resulting in them “being called in far more often to referee disputes.”  Employment site LinkedIn found three years ago that “H.R. had the highest turnover rate of any job it tracked.”  With more and more areas causing problems for them, its staff members often call it a “thankless job.” 

Perhaps fuller and consistently honest disclosure of practices, my largest wish for HR during my corporate career, would help their reputation – but that would be neither quick nor easy.  And so it goes with the other three situations.  People are more willing to accept a fair shake when they know the rules, even if they are not as favorable as they would like.  That is the moral of these stories.

It Looked Like a Positive Jobs Report Month, Despite AJSN Showing Latent Demand Up Almost 400,000 – But Was It?

This morning’s Bureau of Labor Statistics Employment Situation Summary was supposed to be favorable, with published estimates I saw of the net new nonfarm payroll positions with increases of 165,000, 165,000 and 170,000.  Its 256,000 well exceeded those, and most of the other statistics followed.  Seasonally adjusted and unadjusted unemployment fell 0.1% and 0.2% to 4.1% and 3.8%.  The number of unemployed was off 200,000 to 6.9 million, with 100,000 fewer of those out for 27 weeks or longer, reaching 1.6 million.  The count of people working part-time for economic reasons, or thus far unsuccessfully seeking full-time work while holding on to lower-hours propositions, dropped another 100,000 to 4.4 million.  The two measures showing how common it is for Americans to be working or officially jobless, the employment-population ratio and the labor force participation rate, gained 0.2% and stayed the same, ending at 60.0% and 62.5%.  The unadjusted count of employed lost 162,000 to 161,294,000.  Average private nonfarm hourly payroll wages reached $35.69, 8 cents, or slightly less than inflation, more than the previous month. 

The American Job Shortage Number, the metric showing how many more positions could be quickly filled if all knew that getting one would be little more than an ordinary daily errand, worsened with a 359,000 increase, as follows:

Almost all of the AJSN’s increase is probably illusory, as the Census Bureau greatly increased their view of the American population from November 16^th to December 16^th, the dates of record for the AJSN, and so the non-civilian et al. category above, which takes the difference between those included in our population and in any employment category, rose almost 3.4 million.  Accordingly, the share in the AJSN flew up almost as much as the statistic increased.  Otherwise, the fall in those officially unemployed was essentially offset by a gain in those wanting work but not looking for it during the previous year, and there were no other large changes.

Compared with a year earlier, the AJSN grew just over 200,000, with the largest changes from a lower number of expatriates (subtracting 700,000 from the AJSN), more people officially jobless (adding 490,000), more in armed services or unaccounted for (adding 349,000), and more discouraged (adding 127,000). 

So what’s the real story here?  It was good, but tempered by 683,000 net drop in the labor force, which along with 432,000 more claiming no interest, means that too many, perhaps the same people previously stepping back into the job-search world without finding what they wanted, are departing.  Will that be a problem in 2025?  We will continue tracking it, which we need to know before being enthusiastic about improvements mostly attributable to a smaller labor force.  In the meantime, though, the turtle took a fair-sized step forward.