A Rush to the Exits: Forget Immigration, Canada has an Emigration crisis

Canada’s open immigration policy has often been hailed as a positive thing, contributing to the building
of the country. Yet the Trudeau government’s decade-long determination to drive immigration numbers
ever-higher – a policy that public outcry now has it scrambling away from – has obscured an important
and discouraging phenomenon. Every year, tens of thousands of Canadians leave the country, taking
their skills and ambitions with them, and leaving Canada diminished.

Emigration is the flipside of the immigration issue — a side that has been largely ignored. Statistics
Canada estimates that more than 104,000 people left Canada in 2023-2024, a number than has been
rising for the past few years. Another study put the number of Canadian citizens living abroad in 2016 at
between 2.9 million and 5.5 million, with a “medium” scenario of 4,038,700 — or about 12.6 percent of
the Canadian population that year (the latest for which this kind of analysis exists).

This trend isn’t just an abstract problem; it undermines the very economic goals policymakers hope to
achieve through immigration. Emigrants are younger, better educated, and earn higher incomes than
the average Canadian, according to Statcan’s study: “The departure of people with these characteristics
raises concerns about the loss of significant economic potential and the retention of a highly skilled
workforce.” Canada is losing its best and brightest, many of them to the U.S. A survey by the U.S. Census
Bureau this year said the number of people moving from Canada to the U.S. was up 70 percent from a
decade ago.

Canada’s economic decline is big reason for the exodus. In 2022, all 10 Canadian provinces had median
per capita incomes lower than the lowest-earning American state. Canada’s per capita GDP growth has
also stagnated, with projections placing the country dead last among OECD nations out to 2060. Our
productivity is in decline and business investment is moribund, meaning employers in other countries
are able to pay more and compete for qualified labour.

The high cost of living, particularly skyrocketing housing costs, is an increasingly large factor pushing
skilled Canadians abroad. A recent survey by Angus Reid reported that 28 percent of Canadians are
considering leaving their province due to unaffordable housing, with 42 percent of those considering a
move outside Canada.

Even immigrants to Canada are losing faith and moving on. A recent report from the Institute for
Canadian Citizenship, entitled The Leaky Bucket, found that “onward” migration had been steadily
increasing since the 1980s. A follow-up survey of more than 15,000 immigrants and found that 26
percent said they are likely to leave Canada within two years, with the proportion rising to over 30
percent among federally selected economic immigrants—those with the highest scores in the points
system.

“While the fairy tale of Canada as a land of opportunity still holds for many newcomers,” wrote Daniel
Bernhard, CEO of the ICC, there is undeniably a “burgeoning disillusionment. After giving Canada a try,
growing numbers of immigrants are saying ‘no thanks,’ and moving on.” It’s a particularly stark
phenomenon considering that most immigrants have come from much poorer, less developed and often
autocratic or unsafe nations; that these people find Canada – for decades considered the ultimate
destination among those seeking a better life – to be such a disappointment that the best response is to
leave is a damning indictment.

Consider Elena Secara, an immigrant from Romania who built a life here only to find Canada’s economic
reality falling short of her expectations. After nearly two decades, Secara plans to return to Romania, a
country she sees as improving, while Canada, she says, “is getting worse and worse. Canada is
declining…In Romania there are much more opportunities for professionals, the medical system is
better, the food is better.” And, she adds with a laugh, “Even the roads are better.” One of her sons has
already voted with his feet, and is now living in Romania.

That a country like Romania, for years one of Europe’s poorest and most corrupt nations, can now
attract emigrants from Canada should be sobering for policymakers. Canada is facing ever-greater
competition just as it enters the second decade of what may be its longest and most serious economic
deterioration since Confederation.

Each emigrant lost represents not just an individual choice but a systemic failure to provide opportunity
at home. As the revolving door of emigration spins faster, Canada faces a reckoning. Our political leaders
must address the housing crisis, lower tax burdens, and foster a more competitive economy to retain
the talent Canada desperately needs. Without action, Canada’s silent exodus risks becoming a defining
national failure—one that leaves the country less resilient, less innovative, and less prepared for the
future.

The original, full-length version of this article was recently published in C2C Journal.

Scott Inniss is a Montreal writer.

Related Topics:#C2CJournal #CanadaEconomy #CanadaGDP CanadaEconomicDecline CanadaEmigration ScottInniss

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Artificial Intelligence

The Emptiness Inside: Why Large Language Models Can’t Think – and Never Will

Published on December 2, 2025

Todayville

This is a special preview article from the:

By Gleb Lisikh

Early attempts at artificial intelligence (AI) were ridiculed for giving answers that were confident, wrong and often surreal – the intellectual equivalent of asking a drunken parrot to explain Kant. But modern AIs based on large language models (LLMs) are so polished, articulate and eerily competent at generating answers that many people assume they can know and, even
better, can independently reason their way to knowing.

This confidence is misplaced. LLMs like ChatGPT or Grok don’t think. They are supercharged autocomplete engines. You type a prompt; they predict the next word, then the next, based only on patterns in the trillions of words they were trained on. No rules, no logic – just statistical guessing dressed up in conversation. As a result, LLMs have no idea whether a sentence is true or false or even sane; they only “know” whether it sounds like sentences they’ve seen before. That’s why they often confidently make things up: court cases, historical events, or physics explanations that are pure fiction. The AI world calls such outputs
“hallucinations”.

But because the LLM’s speech is fluent, users instinctively project self-understanding onto the model, triggered by the same human “trust circuits” we use for spotting intelligence. But it is fallacious reasoning, a bit like hearing someone speak perfect French and assuming they must also be an excellent judge of wine, fashion and philosophy. We confuse style for substance and
we anthropomorphize the speaker. That in turn tempts us into two mythical narratives: Myth 1: “If we just scale up the models and give them more ‘juice’ then true reasoning will eventually emerge.”

Bigger LLMs do get smoother and more impressive. But their core trick – word prediction – never changes. It’s still mimicry, not understanding. One assumes intelligence will magically emerge from quantity, as though making tires bigger and spinning them faster will eventually make a car fly. But the obstacle is architectural, not scalar: you can make the mimicry more
convincing (make a car jump off a ramp), but you don’t convert a pattern predictor into a truth-seeker by scaling it up. You merely get better camouflage and, studies have shown, even less fidelity to fact.

Myth 2: “Who cares how AI does it? If it yields truth, that’s all that matters. The ultimate arbiter of truth is reality – so cope!”

This one is especially dangerous as it stomps on epistemology wearing concrete boots. It effectively claims that the seeming reliability of LLM’s mundane knowledge should be extended to trusting the opaque methods through which it is obtained. But truth has rules. For example, a conclusion only becomes epistemically trustworthy when reached through either: 1) deductive reasoning (conclusions that must be true if the premises are true); or 2) empirical verification (observations of the real world that confirm or disconfirm claims).

LLMs do neither of these. They cannot deduce because their architecture doesn’t implement logical inference. They don’t manipulate premises and reach conclusions, and they are clueless about causality. They also cannot empirically verify anything because they have no access to reality: they can’t check weather or observe social interactions.

Attempting to overcome these structural obstacles, AI developers bolt external tools like calculators, databases and retrieval systems onto an LLM system. Such ostensible truth-seeking mechanisms improve outputs but do not fix the underlying architecture.

The “flying car” salesmen, peddling various accomplishments like IQ test scores, claim that today’s LLMs show superhuman intelligence. In reality, LLM IQ tests violate every rule for conducting intelligence tests, making them a human-prompt engineering skills competition rather than a valid assessment of machine smartness.

Efforts to make LLMs “truth-seeking” by brainwashing them to align with their trainer’s preferences through mechanisms like RLHF miss the point. Those attempts to fix bias only make waves in a structure that cannot support genuine reasoning. This regularly reveals itself through flops like xAI Grok’s MechaHitler bravado or Google Gemini’s representing America’s Founding Fathers as a lineup of “racialized” gentlemen.

Other approaches exist, though, that strive to create an AI architecture enabling authentic thinking:

 Symbolic AI: uses explicit logical rules; strong on defined problems, weak on ambiguity;
 Causal AI: learns cause-and-effect relationships and can answer “what if” questions;
 Neuro-symbolic AI: combines neural prediction with logical reasoning; and
 Agentic AI: acts with the goal in mind, receives feedback and improves through trial-and-error.

Unfortunately, the current progress in AI relies almost entirely on scaling LLMs. And the alternative approaches receive far less funding and attention – the good old “follow the money” principle. Meanwhile, the loudest “AI” in the room is just a very expensive parrot.

LLMs, nevertheless, are astonishing achievements of engineering and wonderful tools useful for many tasks. I will have far more on their uses in my next column. The crucial thing for users to remember, though, is that all LLMs are and will always remain linguistic pattern engines, not epistemic agents.

The hype that LLMs are on the brink of “true intelligence” mistakes fluency for thought. Real thinking requires understanding the physical world, persistent memory, reasoning and planning that LLMs handle only primitively or not all – a design fact that is non-controversial among AI insiders. Treat LLMs as useful thought-provoking tools, never as trustworthy sources. And stop waiting for the parrot to start doing philosophy. It never will.

The original, full-length version of this article was recently published as Part I of a two-part series in C2C Journal. Part II can be read here.

Gleb Lisikh is a researcher and IT management professional, and a father of three children, who lives in Vaughan, Ontario and grew up in various parts of the Soviet Union.

C2C Journal

Learning the Truth about “Children’s Graves” and Residential Schools is More Important than Ever

Published on December 1, 2025

Todayville

This is a special preview article from the:

By Tom Flanagan

When the book Grave Error was published by True North in late 2023, it became an instant best-seller. People wanted to read the book because it contained well-documented information not readily available elsewhere concerning the history of Canada’s Indian Residential Schools (IRS) and the facts surrounding recent claims about “unmarked graves.”

Dead Wrong: How Canada Got the Residential School Story So Wrong is the just-published sequel to Grave Error. Edited by Chris Champion and me, with chapters written by knowledgeable academics, journalists, researchers and even several contributors who once worked directly in residential schools or dedicated Indian hospitals, Dead Wrong was published because the struggle for accurate information on this contentious subject continues. Let me share with you a little of what’s in Dead Wrong.

Outrageously, the New York Times, the world’s most influential newspaper among liberals and “progressives”, has never retracted its outrageously false headline that “mass graves” were uncovered at Kamloops in 2021. Journalist Jonathan Kay exposes that scandal.

With similarly warped judgment, the legacy media were enthused about last year’s so-called documentary Sugarcane, a feature-length film sponsored by National Geographic and nominated for an Academy Award. The only reporter to spot Sugarcane’s dozens of egregious factual errors was independent journalist Michelle Stirling; her expose is included in Dead Wrong.

In spring 2024, the small Interior B.C. city of Quesnel made national news when the mayor’s wife bought ten copies of Grave Error for distribution to friends. After noisy protests by people who had never read the book, Quesnel city council voted to censure Mayor Ron Paull and tried to force him from office. It’s all described in Dead Wrong.

Also not to be forgotten is how the Law Society of B.C. has forced upon its members training materials that assert against all evidence that children’s remains have been discovered at Kamloops. As told by James Pew, B.C. MLA Dallas Brodie was expelled not from the NDP but from the Conservative caucus for daring to point out this obvious and incontrovertible
falsehood. But the facts are that ground-penetrating radar (used at the former Kamloops IRS) can detect only “anomalies” or “disturbances”, not identify what those might be; that no excavations have been carried out; and that no human remains whatsoever, let alone “215 children’s bodies”, have been found there. Brodie is completely correct.

Then there is the story of Jim McMurtry, suspended by the Abbotsford District School Board shortly after the May 2021 Kamloops announcement. McMurtry’s offence was to tell students the truth that, while some Indigenous students did die in residential schools, the main cause was tuberculosis. His own book The Scarlet Lesson is excerpted in Dead Wrong.

Historian Ian Gentles and former IRS teacher Pim Wiebel offer a richly detailed analysis of health and medical conditions in the schools. They show that these were much better than what prevailed in the Indian reserves from which most students came.

Another important contribution to understanding the medical issues is by Dr. Eric Schloss, narrating the history of the Charles Camsell Indian Hospital in Edmonton. IRS facilities usually included small clinics, but students with serious problems were often transferred to Indian Hospitals for more intensive care. Schloss, who worked in the Camsell, describes how it delivered state-of-the-art medicine, probably better than the care available to most non-native children anywhere in Canada at the time.

Rodney Clifton’s contribution, “They would call me a ‘Denier,’” describes his personal experiences working in two IRS in the 1960s. Clifton does not tell stories of hunger, brutal punishment and suppression of Indigenous culture, but of games, laughter and trying to learn native languages from his Indian and Inuit charges.

And far from the IRS system being a deliberate, sustained program of cultural genocide, as Toronto lawyer and historian Greg Piasetzki explains, the historical fact is that “Canada Wanted to Close All Residential Schools in the 1940s. Here’s why it couldn’t.” That’s because for many Aboriginal parents, particularly single parents and/or those with large numbers of children,
residential schools were the best deal available. In addition to schooling their kids, they offered paid employment to large numbers of Indigenous Canadians as cooks, janitors, farmers and health care workers, and later as teachers and even principals.

Another gravely important issue is the recent phenomenon of charging critics with “residential school denialism.” This is a false accusation hurled by true believers in what has become known as the “Kamloops narrative”, aimed at shutting down criticism or questions. A key event in this process was when NDP MP Leah Gazan in 2022 persuaded the House of Commons to approve a
resolution “That, in the opinion of the House this government must recognize what happened in Canada’s Indian residential schools as genocide.”

In 2024, Gazan took the next step by introducing a private member’s bill to criminalize dissent about the IRS system. Remember, the slur of “denialist” is a term drawn from earlier debates about the Holocaust. Gazan’s bill failed to pass, but she reintroduced it in 2025. Had such provisions been in force back in 2021, it might well have become a crime to point out that the
Kamloops GPR survey had identified soil anomalies, not buried bodies. Frances Widdowson examines this sordid political campaign of denunciation.

As the proponents of the Kamloops narrative fail to provide convincing hard evidence for it, they hope to mobilize the authority of the state to stamp out dissent. One of the main goals behind publication of Dead Wrong is to head off this drive toward authoritarianism.

Happily, Dead Wrong is already an Amazon best-seller based on pre-publication orders. The struggle for truth continues.

The original, full-length version of this article was recently published by C2C Journal.

Tom Flanagan is the author of many books on Indigenous history and policy, including (with C.P. Champion) the best-selling Grave Error: How the Media Misled Us and the Truth about Residential Schools.