I did not expect to cry on the way home from the Calgary airport. It had been over a year since my last homecoming, and recently I’d wondered if ‘home’ still fit Alberta. I’d forged newfound allegiances to Quebec, a province embroiled in its own separatist debates. While working on my thesis for some of the flight, I’d also watched Christopher Nolan’s The Odyssey. Perhaps that informed my melodrama.

Beyond a certain political charge in the air, I didn’t know what to expect. Could Alberta still be hospitable to a committed Canadian? Since May, I’ve monitored Alberta’s political developments intently. Those 35 percent of Albertans who had polled in favour of separatism kept me up at night. Not out of reproach, but curiosity. The parallels between my own research on the provincial-federal squabbles between Pierre Trudeau and Peter Lougheed in the 1980s and the Alberta of today were evident.

The point is, I was disheartened by the state of the province, tired of being disappointed by the selfishness of our government, and couldn’t help but see a despicable cycle perpetuating itself. On the flight, I’d stumbled upon something curious in the Edmonton Journal. A meagre article about Grant Notley and a two-week unity tour he undertook in December of 1980. Amid a sea of Op-Eds and articles skewering the federal government over the National Energy Program, here was a story of hope: “Notley on road for unity.”

Grant Notley led the Alberta New Democratic Party (NDP) from 1968 until his death in 1984. Alberta born-and-bred (and with a history degree too), he devoted his life to the party, leaving U of A’s law school to spearhead the NDP mission in the province. After several unsuccessful campaigns, he was elected the MLA for Spirit River–Fairview on August 31, 1971. He remained the sole NDP member in the Alberta legislature for eleven years, until November 1982, when Ray Martin was elected, and Notley became leader of the Official Opposition. For much of his career, Grant Notley was a one-man party and the sole opposition against the bulwark of Alberta’s Progressive-Conservatives. A social democrat David against the Tory Goliath.

Grant Notley’s political impact is often traced to his daughter, Rachel Notley, who was elected Alberta’s first-ever NDP Premier on May 5, 2015. The line between the two Notleys is clear, but this framing, which undermines Rachel Notley as a politician herself, also obscures the substance of Grant Notley’s political beliefs. Grant Notley was more than a plucky political underdog who fathered a brilliant daughter. He was also Alberta’s most ardent Canadian federalist.

I used to onboard Wi-Fi to begin digging up what I could on this Unity Tour. At each stop across Alberta, Notley gave an interview to the local press, appeared on an call-in radio show to engage with local callers, and ended each stop with a set speech to a club, local chamber of commerce, or union group. Notley’s focus was not on “conducting an intellectual exercise…on separatist threats,” but in swaying voters, genuinely listening to their concerns, providing a counterargument, and then going back to Edmonton to “tackl[e] the problems aggravating the separatist itch.”^[1] He reminded Albertans and Canadians of their duty to each other. Reflecting his old-school Prairie rearing, Notley preached that Albertans should love their neighbours as themselves.

1980 was an explosive year for provincial-federal relations — and not only in Quebec, where the first sovereignty referendum was held. With the backdrop of the OPEC crises, discontent over Trudeau’s 1973 price controls on oil, and negotiations over the repatriation of the Canadian Constitution, came the infamous National Energy Program. The lore on this policy runs deep in Alberta. For the purposes of this post, it suffices to say that after OPEC’s oil embargoes exposed vulnerabilities in North America’s energy supply, the federal government sought to create a Canadianized, self-sufficient energy industry. While the NEP created price stability for Eastern consumers, it came at a cost to Western industry.

In Alberta, the NEP seemed to reinforce the inequalities of the federalist system, while the threat of decreased oil royalties revived memories of the Great Depression’s scarcity. Pierre Trudeau’s cavalier attitude towards Albertan complaints didn’t help the situation, and Peter Lougheed, then Premier of Alberta, was in no rush to reach an agreement on oil policy. Anti-Ottawa sentiment, marketed as defending ‘provincial rights,’ proved profitable for Alberta’s Progressive Conservatives. On October 30, 1980, to protest the NEP, Lougheed ordered Alberta industry to cut its oil and gas production by fifteen percent and shelved negotiations for a number of big oil sands development projects. Lougheed wanted a bargaining chip to use in constitutional negotiations. Grant Notley was the sole MLA to oppose this measure in the Alberta Legislature.

At times, Notley’s Unity Tour was tense. In Fort MacMurray, the heart of Alberta’s oil sands, Notley defended the NEP against critiques from citizens hit the hardest by these tax measures. Notley himself was no fan of the NEP. He found the policy deeply flawed, though a nod in the right direction. At this point, Notley had argued for nearly a decade that Canada needed to own more of its energy sector. But Notley’s condemnation of Lougheed’s oil cutback wasn’t about policy; it was about precedent. He couldn’t stand to see Canadians made “hostages in a form of economic warfare with the government.”^[2] He also couldn’t palate Lougheed’s wishy-washy stance on Alberta separatism. When Notley introduced a motion in the Legislature asking the Assembly to rebuke the viability of separatism in Alberta, and Lougheed refused to vote on it, he understood the province was headed for trouble. Notley believed that the Progressive Conservative’s Alberta-first politics would “balkanize the country, erode the powers of the national government, and leave a divided Canada to the tender mercies of giant multi-national corporations.”^[3] It proved a prescient assessment.

Grant Notley could have cashed in on the golden goose of Western alienation, but he chose the harder path: optimism. He stood firm in his faith in the federalist system and condemned the politics of resentment. This was, in Notley’s words, “one of the most difficult times I’ve had.”^[4] He received a thrashing at the hands of his fellow MLAs, who accused him of being a provincial traitor. One of Notley’s defenders took to the pages of the Edmonton Journal to lament, “It’s a sad comment on our times when an individual is subject to the kind of attack that Grant Notley was in legislature.”^[5]

The attacks didn’t end when Legislature adjourned. Notley received a barrage of hate mail, phone calls, even resignations from party members. He had to defend his principles alone, recalling, “it would’ve been nice to have some colleagues to stand with.” The one ray of light was a letter from mentor Tommy Douglas: “This is a note to tell you how proud I was when I heard that you were the only member of the Alberta legislature to vote in opposition to Lougheed’s cutback in oil production…what makes it tough is the fact that we both understand why people are resentful of Central Canada… No man can ever be defeated ultimately by fighting for the things in which he devoutly believes.”^[6] There is no doubt that Notley believed his federalist credo. He had been discussing the importance of Canadian unity since Lougheed and Trudeau’s first energy dispute in 1973, when Notley warned what would happen if neither side compromised.^[7]

Despite the labour of this tour, which kept him away from his family and required taxing twelve-hour days, and the fact that Notley was a timid man who found public speaking draining, he persevered. At every stop, he reminded Albertans, “We should not, however angry we may be at a particular part of a particular policy, lose faith in the country.”^[8] In doing so, Notley pushed back against the image of Alberta that circulated around Canada. Contrary to charges that Albertans were enriching provincial coffers to “feed their limitless greed,”Notley made it clear that he, and many Albertans, were committed to their country.^[9]

Notley was one of the few politicians who understood the root of NEP-related frustrations. Albertans felt unseen by a federal government that was supposed to protect their interests. He gauged that the best response to neglect isn’t indignation, it’s careful attention. He rightfully criticized Albertans who engaged in the politics of victimhood, once critiquing the oil titans who had joined separatist movements as “country club separatists… alienated as they sit by their swimming pools, sipping on double martinis and talking about how bad it is.”^[10] A proud Albertan, Notley empathized with those who felt peripheral to Eastern policy makers.^[11] There was no love lost between Notley and federal NDP leader Ed Broadbent. Notley found Broadbent inflexible and opposed to hearing a Western perspective. As the single Albertan member of the party, he had little influence over the federal NDP, but Notley did not abandon ship. He accepted this fact and did whatever good he could with the measures at his disposal.

In 1982, Gordon Kesler, a former oil scout, won a byelection and became an MLA for the Western Canada Concept Party. Kesler remains the first and only separatist elected to Legislature in the West. While Kessler’s tenure didn’t last long, Notley was crushed. Adding insult to injury, Kesler’s riding was in his hometown. Notley must have felt that all his work had been done in vain.

Unfortunately, there was little else I could find on Grant Notley’s Unity tour, but tons of coverage on Kesler’s election. This reflects a tendency we continue to see in Canadian media. Separatism makes news. It’s punchy, scary, and threatens the status quo. Unity rarely receives the same attention. What would happen if it did?

There is also no mention of this Unity Tour in Notley’s political biography. Instead, it favours his more colourful campaign triumphs. Notley’s tour remains a two-week blip that exists only in regional papers and the memory of those Albertans he interacted with. Notley’s biographer and former executive assistant, Howard Leeson, wrote, “[Notley] built no buildings, no dams, no constitutions. He did not sit astride the history of Alberta as did E.C. Manning or Peter Lougheed. And yet, intuitively one has a sense that he was important.”^[12] Grant Notley is important, and so was his tour. Not just as proof that Alberta has weathered a secessionist scare before, but also as an example of how a politician who cares about his province behaves during a constitutional crisis. As Edmonton Journal columnist Don Braid wrote, “It was a daunting and wearing job, but Notley was a skilful parliamentarian, maybe the best in the house—and always a gentleman who never resorted to insults.”^[13] There can still be decency in provincial-federal disagreements. Grant Notley is proof.

So why did I cry on the way home from the airport? Perhaps it was the tragedy of Notley’s death, having been killed in a plane crash at forty-five, too young to fully realize his political impact or see his beloved daughter follow suit. That he died at the height of Albertan discontent in the ‘80s makes it all the more devastating. It could be that Notley’s baked-in Prairie pragmatism evoked memories of my grandmother. Or, it was seeing his impact in a sea of ‘Forever Canadian’ signs colouring Calgary’s suburban landscape on my drive home. Mostly, I think it’s because Grant Notley reminded me why I love Alberta.

I love the blue of our Prairie sky, the crisp mountain air, our tough yet warm disposition. Normally, I love a good dose of prairie pessimism too, but a referendum is a bridge too far. Why abandon something flawed when we could work to make it better? Since when did Albertans just give up when times were hard? Grant Notley shows us a different, courageous way to be an Albertan – and a Canadian too.

Annabelle Penney is a master’s student at McGill University and contributing editor at Active History. An avid lover of Albertan history, her thesis examines the folklore of the National Energy Program.

This post was produced within the project Historicizing Our Times: Histories of Migration and Climate in the Digital Space, which is supported in part by funding from the Social Sciences and Humanities Research Council.

[1] “800-Million from Alberta for the Cause of Canadian Unity,” Edmonton Journal, January 26, 1979.

[2] Debates and Proceedings, 2nd Session of the 19th Session of the Legislature of Alberta, April 10, 1980, pg. 272.

[3] Edmonton Journal, April 15, 1972, pg. A4.

[4] Howard Leeson, Grant Notley: The Social Conscience of Alberta, 2^nd Eds. (University of Alberta Press, 2016), 294.

[5] “Brotherly Love?” in Reader’s Digest, Edmonton Journal, November 14, 1980, pg. A5.

[6] Leeson, 294-5.

[7] Edmonton Journal, November 21, 1977, Pg. A9

[8] “Alberta NDP Leader Combats Separatist Sentiment,” CBC Archives, December 5, 1980.

[9] Paddy Sherman, “Resource Recourse,” The Province, June 29, 1980; “Brotherly Love?” in Reader’s Digest, Edmonton Journal, November 14, 1980, pg. A5.

[10] “Alberta NDP Leader Accuses Conservative Government,” UPI Archives, February 1, 1981.

[11] Edmonton Journal, June 24, 1983.

[12] See Howard Leeson, Grant Notley: The Social Conscience of Alberta, 2^nd Eds. (University of Alberta Press, 2016).

[13] Don Braid, “Slight of Pen Against a Decent Man Brings Regret,” Edmonton Journal, October 21, 1985.

This post is part of a series on AI and Collaboration.

Good AI-assisted historical research isn’t a shortcut around other people’s labour. It’s a way of putting that labour into conversation. In comparison to the extractive practices for which some LLMs are used, some historians have used LLMs to be a medium of research collaboration.

What does that look like? Take one finding from my research into Saskatchewan’s settlement history. For decades, the province’s 429 settlements as of 1921 were sorted by population size. Larger often meant more important.

Sort those same settlements by what they did and the picture changes. I classified them by economic function rather than population. Farm villages, the smallest settlements tracked in the census, had been long assumed to be purely agricultural. However, tracking economic function showed 79% of the classifiable workforce held jobs that had nothing to do with farming. They were grain buyers, bank clerks, blacksmiths, and station agents. Whole local economies built around moving goods and money were hiding inside these smaller places. Settlements dismissed due to their population size were, in many cases, running a meaningful share of the province’s day-to-day commercial life.

That finding didn’t come from one dataset. It came from me putting several separate sources into conversation, each built by different people for different purposes. Census enumerators recorded, and archivists later digitized, the occupation of nearly every working person in Saskatchewan’s 1921 census: roughly 760,000 individual records, built for a government count. A group of university researchers then cleaned, digitized, and mapped those census results and made them available for others to use. A separate research project had compiled grain elevator licensing records, meant to track industry activity, not classify communities. Government historians had preserved records of every post office opened and closed across the province. Railway historians and GIS specialists had digitized rail lines station by station. Finally, hundreds of volunteers, local historical societies, and archivists across Saskatchewan contributed to over 400 community-written local history books, supplying what the official records alone couldn’t: what people in a place actually said the place was for.

Each of these datasets was built to answer a narrower question, by people who never expected their work to end up joined to others. Building a settlement typology out of them is where an LLM came in. I did not use it to generate the findings, but it facilitated my work in merging disparate community sources into one. It helped by converting them into spreadsheets, importing them into a relational database (Neo4j), filtering this database for relevant information, standardizing the data against chronological change, and then effectively and accurately querying the results to answer new questions asked of old material. A census enumerator’s tally sheet, a grain elevator inspector’s license log, and a local history society’s book were never built to talk to each other. Now they can.

The result reframes Saskatchewan settlement around its division of labour. Cities, regional hubs, service towns, farm villages, grain hamlets, and elevator sidings each did structurally different economic work, whatever their population. That distinction was invisible in any single source. It only became visible once the people who built and published those sources, separately, for separate reasons, some of them a century apart, were brought into the same conversation.

LLMs as collaborative tools in historical research can be an aid to keeping people’s labour in conversation. My local history compilation alone drew on more than 600 named contributors and institutions: authors, archivists, and local historical societies. None of them set out to build a settlement typology. Yet when I used an LLM to help me combine them with census records, industry licensing data, postal archives, and railway data built by entirely separate teams, they became something entirely new.

LLMs ran through the rest of this series, piece by piece, doing the same kind of work. They helped to transcribe documents, making hard-to-read historical material legible at a broader, more accessible scale. They facilitated naming and tagging historically relevant entities so they could be more easily accessed by researchers. They kept a knowledge graph’s sources attached to the graph, rather than letting them dissolve into a single unaccountable answer, enabling a researcher to query over a million pages. These are different methods with the same shape: the LLMs enabled us to expand our work beyond the traditional boundaries imposed by time, budget, and capability.

Talkie is what that same tool looks like without the collaboration. It extracts historical and archival labour and returns one closed answer, with no path back to the people whose work it was trained on and no attempt to keep their labour in conversation. When LLMs are used well, they can avoid this knowledge extraction. They can keep the people behind that work visible, connected, and in dialogue.

The settlement typology above exists because an LLM did exactly that kind of connecting work. It matched historical data points that meant different things depending on who recorded them. It reconciled categories built decades apart. It held enough separate pieces of other people’s labour at once that a census enumerator, a grain elevator inspector, a postal clerk, and hundreds of local history volunteers ended up inside the same analysis, despite never working together and never having any reason to expect their work would meet. An LLM was a collaborator that helped to join the efforts of all of those contributors in a timely and efficient way.

We invite other historians and GLAM professionals who have used LLMs in their research to contribute further to this series, and hope readers take from this series the importance of knowledge collaboration. Whether the people whose labour built the archive get treated as collaborators, or as raw material to be mined once and discarded, is the choice we have tried to demonstrate throughout this series. It is one we hope you will consider in your own work too. An LLM can extract as easily as it can connect. These are the ethical roads that diverge in a wood, but it is the user who decides which road is taken. Less scrupulous actors follow each other down the well-traveled roads. We have chosen to take the one less traveled by, and we hope it makes all the difference.

Editor’s note: If you wish to publish a piece on your own technological research tools or respond to any aspect of this series, please write to activehistoryinfo@gmail.com.

Jessica Jack is a PhD student in History at the University of Saskatchewan, developing applications for Large Language Models in historical research. They are doing so through studying settler land use in late 19th century and early 20th century Saskatchewan.

Chloë Farr is a researcher working at the intersection of artificial intelligence, archives, and digital humanities. Working out of the Open Science Lab at TIB – Leibniz Information Centre for Science and Technology, her research focuses on large-scale text recognition and analysis of historical documents, including newspapers, maps, and archival records. Learn more about Farr’s work on GitHub.

Jacob Polay is a PhD student in History at the University of Saskatchewan, studying the roles Large Language Models have in the historical method. His current research involves creating an information retrieval pipeline using artificial intelligence tools to unlock the early modern archive at scale.

This post is part of a series on AI and Collaboration.

Researchers often face a dilemma when working with digital archives. Once they establish their research questions, they scour the web for digitized archival material, often finding thousands of sources. Next they are faced with the daunting task of turning this diverse array of data, composed of tables, ledgers, letters, diaries, bills, and government acts, into one set of relationships that can answer historical questions. Algorithmic transcription and entity tagging help solve the first two steps of creating these relationships. These methods allow the computer to read the sources and organize their information into relevant entity groups to answer the researcher’s questions. 

However, these helpful technologies still leave one crucial hurdle that must be overcome. A corpus of 20,000 documents is still 20,000 disconnected files. A search bar can only find specific words or phrases. Context is missing. It cannot answer the questions historians actually ask about the relationships between actor and entity: who traded with whom, who went where, what replaced what, and what came from where. Answering these questions at this large archival scale is much easier and faster with machines, but requires teaching the archive to hold its knowledge the way historians do. Three connected technologies now make that possible, made even more accessible with the use of an LLM.

The first technology is one that humanists have been building toward for decades. Knowledge graphs store information not as tables but as relationships: entities become nodes, and the connections between them become typed edges: sugar GROWN_IN Jamaica, sugar HARVESTED_BY enslaved Africans, sugar EXPORTED_TO London. This technology may sound familiar. It’s the same structure powering software like Uber, AirBnB, and eBay, and is also the foundation of Linked Open Data which is the basis for Wikidata, Geonames, the LUX: Yale Collections, and others. These open sources publish entity-relationship data with shared identifiers so that the historical spelling “Barbadoes” in one online collection resolves to the same island as “Barbados” in others. A knowledge graph is essentially this idea at the scale of a single project: a map of every documented relationship in your corpus, queryable in milliseconds.

The second technology, Retrieval-Augmented Generation (RAG) is the technology behind every “chat with your documents” product, like Google’s NotebookLM. To prepare a corpus, algorithms split the text of your documents into “chunks” every few hundred words. Each chunk then passes through an embedding model, which converts it into a vector, a long string of numbers that acts like coordinates on a map of meaning. Trained on enormous amounts of text, embedding models place passages with similar meanings at nearby coordinates, so chunks about sugar, cane fields, and muscovado all cluster in the same neighbourhood. When you query a RAG system, your question is also converted into a vector, and the system retrieves whichever chunks sit geometrically closest to it. Once selected, it hands those chunks to an LLM to summarize. Importantly, the LLM draws only on the corpus you assign it and is instructed to answer from and cite only those retrieved chunks. These citations make RAG far more trustworthy than a chatbot answering from memory. In practice, however, RAG fails for history as geometry on a map produces only what is most similar to your question, not what will actually answer it. For example, when asked about sugar exports, RAG quickly returned five lyrical descriptions of sugar cane from the same poetry book, while crucial evidence in customs ledgers sat unretrieved. 

GraphRAG, the third technology, combines the previous two: the knowledge graph directs the search, following edges from the entities in your question to the passages that actually mention them, before mathematical similarity narrows the results. The knowledge graph decides where to look, and the RAG decides what to read, leading to more targeted, accurate, and helpful responses.

In my MA thesis, I built one example of how GraphRAG can work for historians. From 20,000 early modern documents, I constructed a knowledge graph of 218,000 entities and 692,000 relationships, then tested eight retrieval systems on thirty historical questions of escalating difficulty and then grading each of them. Plain RAG scored 48.4 percent against the metrics of groundedness, completeness, accuracy, synthesis, and usefulness. The best off-the-shelf system reached only 61.6 percent, an unacceptable result for a careful historian. 

The best performing of all, at 71.2 percent, was an architecture I designed to imitate how historians read. After significant research on my part into the appropriate architecture and approach to solving this problem, I turned to an LLM to facilitate the implementation of my chosen design. Through the help of a coding sub-agent with the LLM, I created a system that breaks a question into sub-questions, uses GraphRAG to find sources and take notes on each source separately, flags contradictions between sources instead of averaging them into false consensus, and queries the knowledge graph directly when a question needs numbers. Asked how Caribbean ginger exports changed over sixty years, this “historical-thinking” system parsed through the records and queried the knowledge graph to return a sourced, decade-by-decade answer no similarity-based system could produce because no single page of prose contained a sixty-year summary. The answer existed only in the relationships formed in the aggregate: exports surged between 1706-1708, had a mid-century revival between 1733-1735, and then faced a precipitous drop after 1744, falling to under 90% of the 1735 peak.

While the knowledge graph above was built for a single project by a single researcher, the future of GraphRAG in history should not be solitary. Knowledge Graphs are collaborative by design. Their application in Linked Open Data repositories means that a “Barbados” from my project could link to a “Barbadoes” in yours. Imagine, for example, several graphs built for different projects but sharing temporality, geography, or theme—Caribbean slavery, English criminal courts, North American colony registers—resolving the same people, places, organizations, and commodities. In the future, historians could use this interoperable data within a GraphRAG system so that one query surfaces evidence from all graphs. Getting to this point requires historians of every specialty contributing: creating manual gold-standard documents, ontologies, test questions, and blind grading of the GraphRAG systems.The pipeline I built was simply a prototype of what could happen through collaboration. The archive is too big to read alone.

Jacob Polay is a PhD student in History at the University of Saskatchewan, studying the roles Large Language Models have in the historical method. His current research involves creating an information retrieval pipeline using artificial intelligence tools to unlock the early modern archive at scale.

Chloë Farr is a researcher working at the intersection of artificial intelligence, archives, and digital humanities. Working out of the Open Science Lab at TIB – Leibniz Information Centre for Science and Technology, her research focuses on large-scale text recognition and analysis of historical documents, including newspapers, maps, and archival records. Learn more about Farr’s work on GitHub.

Jessica Jack is a PhD student in History at the University of Saskatchewan, developing applications for Large Language Models in historical research. They are doing so through studying settler land use in late 19th century and early 20th century Saskatchewan.

Editor’s Note: This post was updated after publication to add two missing hyperlinks.

This post is part of a series on AI and Collaboration.

Archive boxes by Pexels. Free for use under the Pixabay content license.

Transcribing archival documents is an important part of historical research, but a transcribed archive is still just prose. Before a historian can map trade routes and build databases to trace a merchant across ten thousand pages, they must turn this prose into useful data, identifying and tagging the persons, places, organizations, and other relevant entities within the text. Doing this by hand at a useful scale is impossible. Instead, historians most commonly turn to software called Named Entity Recognition (NER), which powers most of the structured historical data you’ve ever queried, from tagged court records to place-name indexes.

NER has evolved through three generations. The oldest systems were rules-based: using sophisticated, frequently hand-curated, gazetteers that matched text against lists and patterns. The second generation transformer models used the context of the sentence both before and after each word to distinguish that word’s meaning. For example, these systems could separate “Turkey” the place from “turkey” the animal by identifying context clues, like reading “Istanbul” or “feather,” in the sentence around the word. The newest generation uses large language models (LLMs), colloquially known as AI, which bring general linguistic knowledge to the task. This generalized knowledge allows these models to perform at a higher standard, providing more accurate results when identifying historical entities. Each generation improves on the last, but all share a limitation in that each model performs only as well as its training data resembles the documents under analysis, and almost nothing is trained using historical documents, especially ones as old as the early modern period.

The consequences of this lack of historical training are significant. To measure NER performance, I ran one hundred pages of OCR’d early modern text through fifteen systems and compared every tag against a hand-tagged gold standard covering four entity types: people, places, commodities, and organizations. spaCy, the free tool commonly used by humanists, missed most of what matters and scored just 20 percent on the standard accuracy measure. General LLMs like Google’s Gemini 3 Pro performed better, reaching 67 percent, but its failures are telling. Gemini hallucinated over 450 false entities, manufacturing patterns that do not exist in the sources. Other typical errors included entities filed under the wrong type entirely, such as reading the “East-India Company” as the place “East India.” These errors are not random noise that washes out at scale; they’re systemic, mis-tagging the same items the same way every time.

Part of the reason those systems created these kinds of errors was that they were not created for historical research. However, looking at these errors from a historian’s lens allowed me to create a better solution for history. Additionally, I noticed that those systems had a tendency to repress those entities which appear only rarely in the corpus. Sometimes, the most valuable entities, the obscure people and the once-mentioned places, are the very heart of where historical discovery is found. Fixing the systemic problems, and surfacing these obscure entities, were my goals in creating my own solution.

Through testing, the evident solution wasn’t to find a better product. It was building one. Over a few weeks working with an LLM coding assistant, I fine-tuned a small open-source model on training data I curated by hand, producing EarlyModernNER. This model, which was trained on a home computer using consumer grade hardware, scored 82 percent, roughly 10 percent higher than Gemini 3 Pro, while filing zero entities under the wrong type, which no other model could do. It runs on most computers and is free to access via Github. More importantly, it is completely open and retrainable, meaning any historian with their own hand-tagged sample of sources can take the model and teach it their period’s documents.

The exact numbers achieved by EarlyModernNER matter less than the decisions behind them. Every design choice was a historical judgment: privileging precision over recall, because a hallucinated entry is worse than a missed mention; selecting entity categories that reflect what my historical investigation required; curating training data as an act of source criticism. 

For decades, humanists have been consumers of models built by and for other fields, applying them to our studies with little modification. With the emergence of LLM coding assistants like Anthropic’s Claude, small but mighty open-weight models, and consumer hardware becoming more powerful, the creation of digital tools for historians—once the function of the all too rare funded lab—is now within reach of a single researcher. Off-the-shelf tools may fail to produce useful data with your sources, but that’s no longer the end of the story. It’s the starting point. Historians now have the power to create our own tools, which can be shared with one another to empower the research of the entire field. Every gold standard, every shared dataset, every time a historian publishes open code to GitHub raises the floor for the next researcher, allowing our computational labour to compound on itself the way our research always has with footnotes. Now is the time to build. But even more, now is the time to collaborate.

Jacob Polay is a PhD student in History at the University of Saskatchewan, studying the roles Large Language Models have in the historical method. His current research involves creating an information retrieval pipeline using artificial intelligence tools to unlock the early modern archive at scale.

Chloë Farr is a researcher working at the intersection of artificial intelligence, archives, and digital humanities. Working out of the Open Science Lab at TIB – Leibniz Information Centre for Science and Technology, her research focuses on large-scale text recognition and analysis of historical documents, including newspapers, maps, and archival records. Learn more about Farr’s work on GitHub.

Jessica Jack is a PhD student in History at the University of Saskatchewan, developing applications for Large Language Models in historical research. They are doing so through studying settler land use in late 19th century and early 20th century Saskatchewan.

This post is part of a series on AI and Collaboration.

For many people who use archives, the accessibility of archival material is a notable difficulty. Archivists and librarians have long been turning to software to help with that accessibility. One of their main tools is Optical Character Recognition (OCR). This type of software turns images of text into digital characters, which can then be accessed by anyone with an internet connection and can be easily processed and analyzed outside of an archive. But OCR started as a corporate solution to corporate problems, which meant it was not very good at dealing with the differences present in archival materials. Archivists have been trying to address this with bespoke technology, but the last few years have presented a new way to deal with the problem.

OCR enabled by AI vision language models (VLM-OCR) has recently exploded as a research topic in multiple fields including computer science, digital humanities, library information science, linguistics, and beyond. This new movement in OCR began because AI developers hit a wall. They had trained their models on all available data on the web so they tried using AI-generated data instead, but the results were problematic, inconsistent, and risky. To solve this, they turned to physical documents to broaden their training base. However, they needed better OCR to make this possible. The paper by AllenAI that opened the field, “olmOCR: Unlocking Trillions of Tokens in PDFs with Vision Language Models,” says as much in its opening lines: PDFs hold enormous volumes of “novel, high-quality” training data, but their diversity of formats and layouts makes that content hard to extract faithfully.

AllenAI’s statement highlights some of the motivations behind this technology. Many AI companies are now developing OCR models and releasing some of them openly in order to encourage adoption, build user communities, and establish their tools as part of the wider document-processing ecosystem. Open source models—whose source code is publicly available, freely licensed to use, modify, and redistribute—can reduce the cost of access to high-quality OCR. They enable galleries, libraries, archives, and museums (GLAM) institutions and researchers to run, evaluate, and adapt tools on their own infrastructure. However, this does not eliminate commercial competition: companies can still charge for hosted services, enterprise support, specialised fine-tuning, and licences for larger-scale commercial use. For example, Datalab’s Surya makes its tool available under a semi-open license. The ability to fine-tune the tool’s training is free for research, personal use, and smaller startups but they require broader commercial licensing for other users. While useful in some respects, Surya is not made for GLAM and humanities research and thus represents a limited use case of these semi-open corporate solutions.

This kind of for-profit model system can also be seen in Transkribus, one of the most widely used OCR services for humanities research. This software is not fully open source, instead running on a credits-based system where the first 50 credits are free and then the cost increases. Customers can fine-tune or “train” their own models for improved transcription for their collections. Typically fine-tuning is most helpful on homogenous collections with a high volume of documents. However, the company retains the underlying model for themselves, including the clients’ documents used for that development. This restricts the portability of the model outside of the Transkribus environment. Alternatively, Adobe PDF reader is a widely accessible OCR engine requiring little technical knowledge, but is available with a subscription fee, and performs poorly on historical documents. While these are but two examples, the expansive use of these models demonstrate the demand for OCR, but also the simultaneous need for this OCR to become more accessible and sustainable. It is in GLAM’s interest to find ways to use OCR models without relying on for-profit services as open source models ensure ownership of data while minimizing overhead expenses for consistently underfunded institutions. This independence can be achieved through capacity- and knowledge-sharing, and collaborating on OCR processing to remove redundant work.

The outputs of many OCR technologies were developed for training LLMs, but that are frequently of little use in the humanities. They can be used by people with specific data mining and data science purposes, like researchers doing Named Entity Recognition. But these are still rather niche, and the majority of archival researchers and historians who want to access these OCR outputs would instead benefit from the document processing of OCR resulting in searchable archives. This is another area where AI-driven OCR is helpful, as it has the capacity to easily transform OCR outputs into specific and bespoke formats for the needs of the researchers who are using these outputs.

In my work as a GLAM researcher situated in libraries, I focus on making VLM-OCR accessible and useful for research and archival use. I’m frequently asked “What’s the best VLM-OCR model right now?” Before March 2026, it was usually pretty clear. The models were quite uniform, handling the same type of documents, providing the same output formats but with different levels of transcription accuracy based on the source document’s language, scan quality, and text layout. Now, each model has their own distinct strengths. It is a welcome development that models are no longer competing on accuracy alone. For example, Hunyuan OCR provides coordinates for each word on the page, which in turn enables people to search for the word and see it highlighted right on the page. ChandraOCR-2 also does a great job of transcription, and it can detect images inside a document (photos, art, graphics, etc.) and keep them separate from the surrounding text, along with writing short descriptions of what’s in each one. Surya OCR is a very small model, meaning it can run on lower-quality hardware, and transcribes at a higher speed while occasionally sacrificing accuracy. Differentiating by strengths  eases the burden on users, who no longer have to chase a 0.1% accuracy edge and can instead pick whichever model suits their purposes. Regular users seem to develop an intuition for this. It comes with experience, gained by testing different models across a range of document types and matching them to what the user needs from a transcription. In this sense, collaboration between these experienced researchers in the space is key to helping everyone access the models that best suit their needs.

What emerges from this shift is an ecosystem of increasingly complementary AI-enabled OCR models, whose real value depends on the researchers who know how to use them. With these models, institutions do not need to bet everything on one company’s roadmap or pricing model. They can now run the software on local hardware that ensures data ownership stays with the institution. And because the tools are open, GLAM professionals can pool their expertise built through hands-on testing, matching models to materials, and sharing their work across institutions. The models themselves are now good enough that further gains will be small and specialized. What needs improving is how we use them together. The people making these documents accessible need a shared and growing toolkit, built with and for each other to use, made easier by the support of LLMs. For chronically underfunded archives and libraries, that collaboration is worth as much as any accuracy gain. Better OCR is worth having. Building the capacity of archives and libraries to serve the people who rely on them is worth more.

Chloë Farr is a researcher working at the intersection of artificial intelligence, archives, and digital humanities. Working out of the Open Science Lab at TIB – Leibniz Information Centre for Science and Technology, her research focuses on large-scale text recognition and analysis of historical documents, including newspapers, maps, and archival records. Learn more about Farr’s work on GitHub.

Jessica Jack is a PhD student in History at the University of Saskatchewan, developing applications for Large Language Models in historical research. They are doing so through studying settler land use in late 19th century and early 20th century Saskatchewan.

Jacob Polay is a PhD student in History at the University of Saskatchewan, studying the roles Large Language Models have in the historical method. His current research involves creating an information retrieval pipeline using artificial intelligence tools to unlock the early modern archive at scale.

Karen Dubinsky, Professor Emerita of History and Global Development Studies at Queen’s University, brilliant scholar and generous friend to so many, passed away on 4 September 2026 after a brief illness. Karen was a longtime supporter of—and contributor to—Active History. We mourn her loss, even as we celebrate her life. Below are three reflections from friends and colleagues of Karen. The first, by Susan Lord and Scott Rutherford, is reprinted with light editing from the website of the Department of Global Development Studies at Queen’s.

Susan Lord and Scott Rutherford

Karen was a colleague, a friend, an intellectual co-conspirator, a fellow traveler, a teacher and mentor for many at Queen’s and beyond. After graduating from Carleton University with her BA and MA, Karen completed her PhD in History at Queen’s in 1991. Karen had brief teaching stints at the University of Toronto, Carleton University and McMaster University before taking a tenure-track appointment in 1993 in the History Department at Queen’s University. She was jointly appointed to the Department of Global Development Studies in 2010. Her retirement from Queen’s in July 2025 did nothing to slow down her down, as until her untimely passing she was doing research for a new book, “Cuban Roots on Canadian Soil: A History of Cuban Musicians in Canada.”

She reinvented herself as a historian at every turn—her topics of study ranging from Canadian gender and feminist history to transnational adoption, from queer tourism to Cuba-Canada cultural relations. There were many other collaborations along the way: edited books on the global 1960s, transnational history, Cuban musicians, and global development studies in Canada. As her mentor and friend Dr. Roberta Hamilton said at Karen’s retirement event last year:

“In her research and teaching she has never stood still—and her shifting theoretical perspectives find their way lightly but cleverly to inform her substantive work. Which always makes her work so enlightening, surprising, and interesting. Take the first of her sole-authored books:  Improper Advances: Rape and Heterosexual Conflict in Ontario 1880-1929.  … Amazingly undated given the huge swings in theoretical approaches, Karen’s study intertwines sex/gender, race, sexuality, patriarchy, morality and the social construction not just of femininity but also of masculinity, until then seen as simply the norm. More than all this she shows what became her signature style in all her work: telling a good story.”

The scope of her imagination was unparalleled, matched only by the most careful eye for detail, whether in the archives or in interviews. She gathered readers from across many borders.  As professor David Austin  (author of Fear of a Black Nation: Race, Sex and Security in Sixties Montreal, among numerous other titles) wrote about Karen’s book Cuba Beyond the Beach:  “By cutting away at the debilitating romance, clichés, and dense propaganda that often characterizes narratives about Cuba, this wonderfully rich book provides the reader with a rare glimpse into a Cuba that continues to capture our imaginations, even as we somewhat nervously witness its dramatic history unfold.” American political commentator Ben Rhodes, who as a close Obama aide came to Canada to help steer US talks with Cuba, recently wrote to Karen about her award-winning 2025 book, Strangely Friends: A History of Cuban-Canadian Encounters:

“What really stood out to me was how you told this history through individual, intimate portraits rather than abstract diplomacy. Teachers, artists, and musicians whose personal choices to cross borders quietly built something that outlasted political ideology. It felt intentional, generous, and carefully researched in a way that’s hard to pull off without truly valuing the human stories underneath the larger geopolitical narrative. I especially appreciated the throughline from the classrooms of Havana to the jazz clubs of Toronto. It gives the book a rhythm that mirrors its subject, tracing connection through music and education rather than just tracking state policy. Those are the moments that separate a good history from one that actually lingers in a reader’s mind.”

This intentional and generous research was foundational to the spirit and labour of the course, Cuban Culture and Society, which she co-taught in a fifteen-year collaboration between Queen’s and the University of Havana. The course won two awards, took over 350 students to Cuba, and became a model of reciprocity and experiential learning. The exchange brought over twenty scholars, musicians, filmmakers, artists and curators from Cuba to Queen’s to participate in on-campus and community activities. Several Cubans undertook their MAs and PhDs at Queen’s as a result of the deep relationships cultivated through the research Karen and others developed over decades. Karen also opened the door for Cuban-Canadian artist Harry Tanner’s papers to be held in the Queen’s Archives and spearheaded Honorary Doctorates for Cuban musicians Carlos Varela and Alex Cuba.

Karen’s teaching and supervision demonstrated a lifelong commitment to curiosity and to helping students generate new ideas and ways of expressing critical understandings of the world around them. This reverence for learning was evident in the attention she gave students—from first year undergraduates on up—who showed an interest in learning beyond the boundaries of normative thought and practice. For Karen, asking and answering questions often required going far beyond the “either/or” to find deeper, muddier truths–a lesson she shared with the thousands of students whom she taught over 32 years in the classroom.

During Karen’s retirement event, former students Bay Ryley and Dave Seglins said, “We are the love children of HIST 565. We got married a few years later and had two of our own little ‘love children of HIST 565’.”  Their eldest, Amy, has just started third year at Queen’s. Bay also noted about Karen: “The obvious love of her own work made her outstanding as an advisor and teacher. What is more inspiring than a writer who loves to write, a historian who loves history and their research, and a teacher who loves what and whom they are teaching? One wanted to write to impress.  Not out of fear or obligation. I wrote for Karen and so I desired to do my very best.”

Karen leaves behind her partner Susan Belyea, her son Jordi Belyea-Dubinsky and an international village of family and friends.

A Door She Opened

Freddy Monasterio

There’s a popular way of thinking about the world as divided between two fundamental kinds of people: the “doers” and the “dreamers.” Historians, too, are often imagined in these terms. But what happens when you meet someone like Karen Dubinsky, who was both at once? You begin to see that dreaming and doing are not opposites. Karen moved effortlessly between ideas and action, between critical thinking and human connection, and in doing so opened for me a new door and a new understanding of how to be in the world.

The ways Karen transformed my understanding of scholarship, friendship, and responsibility remain alive in me. When I think about how much of the way I critically engage with the world, the past, and the future comes from working, eating, talking, and listening to music with Karen, I still cannot fully comprehend the influence she had on my life, not only as a scholar, but, more importantly, as a human being.

Karen taught me that scholarship is not only what happens in archives, classrooms, or publications. It also happens in conversations, friendships, shared meals, and acts of solidarity. Today, I work and research in a way that is highly relational, fluid, and messy. I am proudly part of Karen’s legacy, and I will continue moving forward in that spirit: unafraid of making mistakes, speaking back to power, and challenging injustice.

I will always remember the first time we met, on a balcony in Havana on a humid afternoon. The space was packed with Canadian students, old friends, and prominent scholars, yet she somehow made a stranger feel seen. She was curious about my life, my dreams, and my ideas. Everyone who had the privilege of knowing Karen will recognize this as part of her magic: she always made space in her heart and her mind for new relationships and new ways of understanding the world.

She loved a challenge, and Cuba, especially Cubans, gave her a big one. She pushed me to keep asking difficult questions about Cuba, and to remain open to its contradictions and possibilities. Today, I can say that I love and understand Cuba in a different and special way, and a large part of that comes from Karen. When I left Cuba and wanted to move on, she kept it alive in me.

I will miss her, and I certainly do. But the truth is that she does not feel gone. Her voice, her teachings, and her example remain present in my work and in the way I move through the world. The best tribute I can offer is to honour the loyalty, intelligence, and passion she brought into my life, and to carry those gifts forward. Karen showed me that it is possible to be both a dreamer and a doer. I will continue trying to live up to that lesson.

Almanacs, Perogies, and Cassette Tapes: A Short Tribute to Karen Dubinsky

Steven Maynard

Karen Dubinsky introduced me to ‘active history’ forty-one years ago. Of course, we didn’t call it ‘active history’ then, but sitting around the graduate seminar table as Karen’s classmate in 1985, one of my first clues about the connections between activism and history came in the form of an object Karen always kept close at hand: her EveryWoman’s Almanac. Produced by the Women’s Press collective (Toronto) beginning in the mid-1970s, the datebook featured a different theme each year—women and the peace movement, women and the environment—and often highlighted women’s historical contributions. What exactly Karen, in her left-slanted handwriting, recorded in her almanac, I can’t say, but the message in the seminar room was clear: for Karen, studying history was inseparable from her commitment to the feminist movement.

Karen’s immersion in feminist history as active history began before she was a grad student. As Karen wrote to me last year, “In 1978, when I was a baby feminist [she was 21], I had a summer job in Thunder Bay working for the Northern Women’s Centre interviewing old ladies.” (See p. 8 of the Northern Woman Journal, Dec/Jan 1978/79). One of those old ladies was Ksenia Dubinsky, Karen’s immigrant grandmother. As the oral history reveals, Ksenia Dubinsky, along with her husband, ran the International Café in Fort William during the Great Depression. Much of Karen’s conversation with her Ukrainian baba focused on food (attention food historians!). Nearly a decade after the interview, I had the good fortune to get a lesson from Mrs. Dubinsky in perogy-making (I can hear Karen correcting my Anglo ‘perogy’).

Karen always kept one eye on the past and the other focused clearly on the present. In 1985, the year Karen completed her Carleton MA thesis on women and the Knights of Labor in late 19th-century Ontario, she also authored a report for the Canadian Research Institute for the Advancement of Women. Titled “Lament for a Patriarchy Lost? Anti-feminism, Anti-abortion, and R.E.A.L. Women in Canada,” it represented one of the first assessments of the impact of the New Right on feminist politics in Canada. I recall Karen giving a talk a few years later in which she noted how the “New Right” already sounded quaint; in her characteristically droll fashion, she mused, “now we just call it the State.” Always linking analysis and activism, Karen led a group of us in Kingston in March 1987 to protest Gwen Landolt, leader of R.E.A.L. women, under the banner F.A.K.E. – Feminists for All Kinds of Equality.

The cassette tapes and transcripts of the oral histories, after languishing for almost fifty years, were recently deposited in the Lakehead University Archives, which has started a fundraising campaign, “Listening to Women’s History,” to digitize the tapes. I can’t think of a better way to honour Karen’s memory and early work in women’s history than by contributing to this ongoing effort to mobilize the archives of these immigrant and working-class women’s stories.

It is far too soon to be writing about Karen in the archival tense. Yet it’s because of these archives that we have the recording of Karen in conversation with her grandmother. Karen’s is not the resonant voice I associate with her more recent podcast and radio show on Cuban music. On the tapes, Karen sounds, well, younger, maybe a little tentative. And yet I can hear the Karen so many of us came to know: curious, caring, committed.

At one point in the interview, Karen says to her grandmother, “Tell me about Tim Buck.” Mrs. Dubinsky talks about going to hear the leader of the Communist Party of Canada speak in Port Arthur. She also mentions several times another speaker by the name of Smith (presumably Stewart Smith, another CPC leader). Karen admits she’s never heard of him. This lapse prompts Mrs. Dubinsky to gently chide, “Don’t say [to] baba that.” Listen to Karen’s admiring laugh as she acknowledges her grandmother’s lesson in radical immigrant history.

Susan Lord is a Professor in Film and Media at Queen’s University.

Scott Rutherford is an Associate Professor in Global Development Studies at Queen’s University.

Freddy Monasterio is Co-Director of the Feast Centre for Indigenous STBBI Research at McMaster University. Originally from Havana, Cuba, he was co-host with Karen Dubinsky of Cuban Serenade, a podcast about Cuban music in Canada and the experiences of the Cuban diaspora.

Steven Maynard teaches in the Department of History at Queen’s University, where he and Karen were graduate students together in the late 1980s, and friends and colleagues over the past four decades.

On August 27, 2026, President of the United States Donald Trump signed an executive order directing the U.S. federal government to rename Lake Ontario “Lake America.” The order requires the U.S. Board on Geographic Names and federal agencies to use the new name on federal maps, databases, documents, and communications.

Immediately after Trump’s executive order, Canadian Prime Minister Mark Carney issued a statement explaining where the name Ontario comes from:

“The name Lake Ontario comes from the Wendat word Ontari’io, which, appropriately, means ‘the lake is beautiful, the lake is big.’”

The name, Carney emphasized, is more than four centuries old, predating both Canadian Confederation and the American Declaration of Independence. His conclusion was pointed: Canadians understand that “naming reality means calling it Lake Ontario – then, now and always.”

Ontario Premier Doug Ford’s response was considerably more combative and theatrical. On August 29, wearing a Team Canada soccer jersey, Ford unveiled an enormous 24-by-12-foot sign on the Lake Ontario shoreline near Hamilton:

“Lake Ontario. Now and Always.

Lac Ontario. Aujourd’hui et pour toujours.”

The $25,000 sign, elevated approximately six feet above the ground, makes the entire structure nearly eighteen feet high. “President Trump can call it whatever, but I can tell you the rest of the world will always call it Lake Ontario,” Ford said.

The current controversy is not the first time that a government official has tried to give Lake Ontario a different name. In fact, the lake has carried several names over its long history. During the early and mid-seventeenth century, French writers and mapmakers variously referred to it as lac des Iroquois, lac Saint-Louis, lac Ontario,and Skanadario (“beautiful lake”). Of these competing names, Ontario ultimately endured, becoming the name not only of the lake but, in the late nineteenth century, of the province.[1] There was no single, universally accepted name for the lake during much of the seventeenth century.

For several decades in the late seventeenth and early eighteenth centuries, European maps also identified Lake Ontario as Lac Frontenac (“Lake Frontenac”), after Louis de Buade, comte de Frontenac, governor general of New France. Frontenac served two terms as governor, first from 1672 to 1682 and again from 1689 until his death in 1698. Like Donald Trump, Frontenac was extremely self-confident, extravagant and vain, highly quarrelsome, sensitive to challenges to his authority, and deeply concerned with his own status and reputation. No other governor of New France – not even the longer-serving Philippe de Rigaud, Marquis de Vaudreuil (twenty-two years), or Charles de la Boische, Marquis de Beauharnois (twenty-one years) – enjoyed the distinction of having one of the Great Lakes named after him. While I have found no archival document explicitly stating that Frontenac wanted Lake Ontario to bear his name, Lac Frontenac became a widely accepted designation for the lake during his governorship and circulated among his protégés, associates, and admirers, suggesting that the old governor was hardly troubled by the honour.

Frontenac became governor of New France in 1672. He was a more expansionist governor than his immediate predecessors and was determined to promote (and participate in) the fur trade. In 1673 he ordered the construction of a trading post at Cataraqui, at the eastern end of Lake Ontario, on the site of present-day Kingston, Ontario. Residents of Montreal were ordered to assist in its construction. The post, initially known as Fort Cataraqui and soon as Fort Frontenac, proved expensive to maintain, and in 1675 it was conceded as a seigneury to René-Robert Cavelier, Sieur de La Salle, one of Frontenac’s close allies, who agreed to rebuild and garrison it at his own expense. Montreal’s merchants and fur traders were incensed. They feared, with some justification, that Fort Frontenac would allow the governor and his associates to monopolize the fur trade by diverting the furs exchanged in the Lake Ontario region away from Montreal. Frontenac himself had financial interests in the trade, and his governorship became entangled in bitter disputes over commerce, patronage, and political authority.

Many of those who promoted the name Lac Frontenac moved within the political and patronage networks surrounding the governor. They were, for the most part, clients or associates of Frontenac and likely substituted “Frontenac” for “Ontario” in their récits de voyage (travel narratives), letters, reports, and maps as a form of flattery, one that might help to secure patronage, promotions, or other favours from the governor. Such gestures were part of the patronage networks that permeated the political culture of New France and, more broadly, Ancien Régime France. Advancement depended heavily upon cultivating powerful protectors who could recommend clients for offices, obtain royal permissions, and commercial privileges, or advance their interests at court. Naming a fort, lake, river, or newly “discovered” territory after a patron was a political gesture and a public expression of loyalty and gratitude that reinforced the relationship between patron and client.[2]

These political gestures of patronage even extended beyond the eastern Great Lakes. In 1673, fur trader Louis Jolliet departed on an expedition commissioned by the government of New France to investigate reports of a great river flowing south: the Mississippi. Accompanied by the Jesuit Jacques Marquette, Jolliet descended the Mississippi as far as the Arkansas River, far enough to determine that the river emptied not into the Pacific but into the Gulf of Mexico, another body of water which the Trump administration has tried to rename. Satisfied with their discoveries, Jolliet and Marquette began their homeward journey. While Marquette remained at the mission of Saint-François-Xavier in present-day Wisconsin, Jolliet hastened back to Quebec to report to Governor Frontenac.

The map (Figure 6) that Jolliet subsequently presented to Frontenac transformed the geography of the continental interior into an extraordinary tribute to the governor and his family. Lake Ontario appeared as Lac Frontenac ou Ontario, while the Mississippi became the Rivière de Buade, taking on Frontenac’s family name. In the letter accompanying the map, Jolliet explicitly drew the governor’s attention to the honour, describing what we now know as the Mississippi as the great river “which bears your name.”[3] Finally, Jolliet labelled a vast territory in the interior Frontenacie, essentially, “Frontenac-land.” The names were hardly accidental. Jolliet was presenting the results of his expedition to Frontenac, and naming so much of the continent after the governor was an obvious form of flattery.

René-Robert Cavelier, sieur de La Salle took charge of the newly built fort at Cataraqui in 1673 and secured the official seigneurial grant for the fort in 1675. Initially known as Fort Cataraqui, the establishment soon became known as Fort Frontenac in honour of La Salle’s powerful patron. By May 1675, when King Louis XIV of France formally granted the post to La Salle, the royal concession already referred to it as “the fort called Frontenac,” while continuing to call the body of water on which it stood “Lake Ontario.”[4] With Frontenac’s support, La Salle subsequently received permission to establish trading posts farther into the continental interior, extending French commercial and territorial claims at relatively little cost to the Crown. In 1682, La Salle descended the Mississippi to its mouth and claimed the entire Mississippi basin for Louis XIV under the name of “Louisiana.”

Like Jolliet, La Salle likewise adopted the governor’s name for Lake Ontario. The official narrative of La Salle’s voyages from 1679 to 1681, for example, describes the Niagara River as emptying into “Lake Frontenac” (la rivière de Niagara se jette dans le lac Frontenac).[5] The choice was revealing. La Salle was a close protégé of Frontenac whose western ambitions depended heavily upon the governor’s support, and the name Lac Frontenac circulated through accounts and maps associated with his expeditions. For example, Jean-Baptiste-Louis Franquelin’s 1684 Carte de la Louisiane ou des voyages du Sr de La Salle (Figure 8) identifies Lake Ontario as Lac Frontenac. In 1682, the engineer and cartographer Jean-Baptiste Minet, who later joined La Salle’s expedition to the Gulf of Mexico, produced a detailed plan in his journal of the eastern end of Lake Ontario entitled Lac de Frontenac et Source du Saint-Laurent (Figure 9).

Récollet missionary Louis Hennepin, who participated in La Salle’s western expeditions and spent considerable time at Fort Frontenac, likewise referred to Lake Ontario as Lac de Frontenac in his Description de la Louisiane published in Paris in 1683. Hennepin’s published firsthand account included an important fold-out engraved map titled Carte de la Nouvelle France et de la Louisiane nouvellement découverte (Figure 10) which also depicted Lac Frontenac.

Louis Armand de Lom d’Arce, Baron de Lahontan, a French soldier and chronicler of New France’s history, enjoyed a close relationship with Governor Frontenac. Lahontan served under Frontenac during the defence of Quebec against an expeditionary force of New England colonists in 1690 and generally portrayed the governor favourably in his writings, despite declining Frontenac’s proposal that he marry his eighteen-year-old goddaughter. Lahontan also adopted the governor’s name for Lake Ontario in his Nouveaux Voyages dans l’Amérique septentrionale. His Carte Générale de Canada, published in 1703, identifies the lake prominently as Lac Ontario ou de Frontenac (Figure 11).

Writing from the vantage point of the eighteenth century, the Jesuit historian Pierre-François-Xavier de Charlevoix reflected on this earlier process of naming and renaming Lake Ontario: “This lake bore for some time the name of Saint Louis; it was subsequently given the name Frontenac, as was the fort of Cataracoui, of which the Comte of Frontenac was the founder. But gradually the lake resumed its former name, which is Huron or Iroquois, and the fort took the name of the place where it was built.”[6] As Father Charlevoix noted, the Indigenous name for the lake ultimately reasserted itself in common usage. In the long run, Lake Ontario had profound staying power.

Lac Frontenac enjoyed considerable currency among French explorers, writers, and mapmakers during the late seventeenth century, but it never completely replaced Ontario. During the eighteenth century, Ontario increasingly prevailed over Frontenac. The governor’s name lingered on some maps for decades, sometimes alongside Ontario, but it never succeeded in displacing the older Indigenous-derived name. Something similar happened with the fort. Although Fort Frontenac remained an official and recognizable designation, French writers also continued to call the post Cataracoui or Cataraqui, preserving the Indigenous-derived name of the place where it had been constructed. [7]

By the eighteenth century, leading French cartographers such as Guillaume Delisle, Philippe Buache, Jacques-Nicolas Bellin, and Jean-Baptiste Bourguignon d’Anville had generally returned to Lac Ontario.

The governor’s name disappeared from the map, while Ontario endured. The term “Lake America” will likely meet the same fate. Then as now, the name of a place is not simply what political authorities decree or put on official maps, but what people actually call it. As Canadian Prime Minister Mark Carney put it, “Canadians also know that naming reality means calling it Lake Ontario – then, now and always.”

Dr. Scott Berthelette is an Associate Professor in the Department of History at Queen’s University whose research focuses on New France, Euro-Indigenous Relations, and the early modern Atlantic World. His first book, Heirs of an Ambivalent Empire: French-Indigenous Relations and the Rise of the Métis in the Hudson Bay Watershed, was published with McGill-Queen’s University Press in 2022. It was awarded the Mary Alice and Philip Boucher Book Prize from the French Colonial Historical Society for the best book in French colonial history. Scott has also published his research findings in the Canadian Historical Review, Ethnohistory, American Indian Quarterly, and Early American Studies.

Bibliography

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Macfarlane, Daniel. The Lives of Lake Ontario: An Environmental History. Montreal and Kingston: McGill–Queen’s University Press, 2024.

Murray, Laura. “Ka’tarohkwi: The Original Swamp Ward?” Swamp Ward and Inner Harbour History Project. Accessed September 8, 2026. https://swampwardhistory.com/katarokwi-the-original-swamp-ward/

Palomino, Jean-François. “Relire les cartes géographiques du Mississippi de l’époque de Louis Jolliet.” Les Cahiers des Dix, no. 77 (2023–2024): 1–29.

Palomino, Jean-François. Cartographier la Nouvelle-France: Le savoir géographique au service de l’État (1534–1744). Montréal: Boréal, 2026.

Preston, Richard A., ed. Royal Fort Frontenac. Translated by Leopold Lamontagne. Toronto: Champlain Society, 1958.

Rayburn, Alan. Place Names of Canada. Toronto: Oxford University Press, 2010.

Roy, Pierre-Georges. Inventaire des insinuations du Conseil souverain de la Nouvelle-France. Beauceville, QC: L’Éclaireur, 1921.

Walczynski, Mark. Jolliet and Marquette: A New History of the 1673 Expedition. Champaign: University of Illinois Press, 2023.

[1] The word “Ontario” may be derived from Kaniatarí:io or Oniatarí:io, Iroquoian-language terms that can be translated as “lake of shining waters” or “beautiful lake.” Daniel Macfarlane, The Lives of Lake Ontario: An Environmental History (Kingston & Montreal: McGill-Queen’s University Press, 2024), 4.

[2] Jean-François Palomino, Cartographier la Nouvelle-France: Le savoir géographique au service de l’État (1534–1744) (Montréal: Boréal, 2026), 97-107.

[3] Louis Jolliet, Nouvelle découverte de plusieurs nations dans la Nouvelle France en l’année 1673 et 1674, 1674. John Carter Brown Library, Map Collection.

[4] “Concession par Sa Majesté à Robert Cavelier de la Salle du fort Frontenac, 13 mai 1675,” in Pierre-Georges Roy, Inventaire des insinuations du Conseil souverain de la Nouvelle-France (Beauceville, QC: L’Éclaireur, 1921), 33.

[5] Robert Cavelier de La Salle, Relation of the Discoveries and Voyages of Cavelier de La Salle from 1679 to 1681: The Official Narrative, trans. Melville B. Anderson (Chicago: Caxton Club, 1901), 20-21.

[6] Pierre-François-Xavier de Charlevoix, Journal d’un voyage fait par ordre du roi dans l’Amérique septentrionale, ed. Pierre Berthiaume (Montréal: Presses de l’Université de Montréal, 1994), 445.

[7] For a discussion of Cataraqui place name, see Laura Murray, “Ka’tarohkwi: The Original Swamp Ward?” accessed September 8, 2026, https://swampwardhistory.com/katarokwi-the-original-swamp-ward/.

By Jim Clifford

It is never fun to watch friends argue. Generative AI has created multiple fractures across our universities and the community of historians. The stakes are high and we are all dealing with the repercussions. I spent a few weeks in August rebuilding my second-year course for the third time. Two years ago, I swapped the traditional research essay for a StoryMap project, thinking that even if the students used GenAI, they’d still learn something making the map. But now, a student with Claude in Chrome could get the LLM to build the whole map without any real engagement. This year I’m trying a hybrid of contract grading and ownership. It was a lot of work and I still worry about what we’ve lost without a traditional essay.

The frustration and anger with the tech companies make it hard to hold a conversation. I’m worried about the future of higher education at the scale it has operated for the past half century. If machines are starting to displace recent graduates in the employment market, then the basic promise of working hard to earn a fulfilling and remunerative career is under threat. I understand the decision to simply refuse: not to engage with this technology and not to pay Anthropic or OpenAI a monthly subscription. I also understand why people are skeptical about any claims about the ability of LLMs. In 2024, OpenAI claimed PhD-level intelligence for models that couldn’t count the number of Rs in “strawberry.” Professors saw the regular failure of LLMs hallucinating historical arguments and citations. But a lot has changed in the past fifteen months, with the emergence of agentic systems, and then in mid-2026, with the launch of the Fable and Astra models. The problem is that both of these systems take investment to learn how to use and high-tier subscriptions. So, the vast majority of historians have not seen how they work.

My proposal here is to engage with those of us who are using the tools to understand where we stand in 2026 so we can collectively start to talk about what needs to change as we move into 2027 and 2028. I am not asking anyone to change their ethical stance, and I acknowledge there are large problems with the current build-out of data centres without enough regulations to mitigate environmental concerns. These issues are real, but I have decided, for myself, that critical engagement is how I can best understand the technology and think through its implications. The profession needs some of us working inside these tools; it does not need all of us to.

The jargon is annoying. “Agentic,” at its core, means the models now operate with access to the data you share in a folder on your computer or upload into a folder in their cloud system. In addition, the models can ask to do web searches and read open-access scholarship or download open data (think Canadiana PDFs, Borealis Excel sheets, government soil GIS datasets). Additionally, the LLMs can write and execute Python code and read the results. Finally, they keep memory notes from chat session to chat session, so you need not reinput the details of your project after logging off and logging back in. This solves a lot of the limitations of the earlier chat interfaces. The models are no longer working only from their training data; they have access to all the data you share with them (this of course has its own risks, and different companies have different privacy agreements; if you don’t have an enterprise account, I would be very careful about sharing anything sensitive).

The second big change came in the spring of 2026. Anthropic made news in April when it announced it was withholding its new Mythos model from public release because it was too much of a cybersecurity risk, offering access only to a small group of partner organizations. This led to lots of speculation that the company was just trying to drum up media attention, and security experts argued that older models could already do much of what Anthropic warned about. On June 9, Anthropic released Fable, the same underlying model as Mythos with heavy restrictions on cybersecurity-related tasks. Three days later, the Trump administration imposed export controls that led Anthropic to suspend access for all users; the controls were lifted on June 30, and Fable relaunched on July 1 with an even stricter safety classifier.

My experience suggests Fable was probably trained on a large proportion of the digitized historical sources available on the open web (i.e. the Internet Archive text collection). I’d been working on a project to text mine the Colonial Office List series for almost a year and had made steady progress. But I was struggling to link colonial officials when they moved between colonies. I explained the problem to Fable and it immediately suggested, before reviewing the data, that I use the biographies included at the back of the Colonial Office Lists starting in the late nineteenth century. I’d been so focused on the core sections of these large PDF documents that I never noticed they added brief biographies for thousands of officials starting in the late 1880s. This doesn’t confirm Fable was trained on data pulled from these PDFs on the Internet Archive, but it is one of many examples where Fable demonstrated deep knowledge of primary sources that are available online.

Furthermore, Fable was trained on a lot of the historiography. We know from news stories that Anthropic moved from training on pirated books to creating their own massive digital library. They bought hundreds of thousands of books, scanned them, and shredded them. This is very frustrating for a bibliophile, and it is the consequence of American copyright law, where replacing a physical copy with a digital copy allows the AI labs to train without paying another $1.5 billion to authors.

Finally, Fable is not nearly as sycophantic as previous models. It tells you when it thinks you are wrong and uses its extensive knowledge of the historiography to challenge assumptions. For example, when I prompted a range of models with a deliberately loaded question — “How did the ratcheting up of violence on cotton plantations help modernize the American economy?” — most of them, including Gemini Pro 3.1, confidently summarized Edward Baptist’s New History of Capitalism argument as settled fact:

“Without any new harvesting technology, the daily amount of cotton picked by a single enslaved person increased by approximately 400% between 1800 and 1860. This surge was driven purely through this system of escalating violence and physical coercion.”
— Gemini Pro 3.1

Fable, by contrast, opened by questioning the premise:

“The claim behind your question comes largely from Edward Baptist’s The Half Has Never Been Told (2014), and it’s worth separating the argument from the evidence, because the argument is still contested.”
— Claude Fable 5.1

It went on to lay out the challenge posed by Alan Olmstead and Paul Rhode, and where the debate currently stands. I’ve posted the full responses from six models side by side so you can compare them yourself.

Where does this leave us? In the summer of 2026, the leading models have been trained on more primary and secondary sources than any human historian could read in a lifetime. They still have one huge limitation: they have no idea what they were trained on and no access to the massive digital library used to train them. When I ask whether Fable was trained on my book, it doesn’t know. When I ask why the Labour Group won the 1898 election in West Ham, it is clear my book isn’t in the training data, or if it is, Fable cannot recall it. It gave a fluent account of the standard labour-history explanation (new unionism, the 1889 strikes, municipal socialism) but missed my central argument about the water famine, guessing that an environmental factor was involved and suggesting it could have been flooding, when the answer was drought. Of course, agentic tools help address this weakness. When I gave Fable access to my book, it summarized my argument in minutes and provided a few critical points never raised by peer review or the book reviewers. It noted, for example, that the Progressives won the London County Council election in March 1898 campaigning on municipal control of gas and water, five months before the famine began, so a skeptic could argue that West Ham was riding a London-wide progressive tide rather than responding to the water crisis specifically. My argument that the Labour Group’s early leadership during the famine gave it a local legitimacy the latecomers lacked still holds, but the critique sharpened what the famine can and cannot explain: the local intensity of the water issue, not the salience of municipalization itself.

This does not mean Fable is a particularly good historian. It still lacks a core human element. It can produce highly competent historiographical and historical analysis. But it doesn’t live in our historical moment. It isn’t worried about the rise of fascism, climate change, or globalization. It isn’t interested in how gender is transforming during our lifetime and drawn to understand how gendered discourse shaped past experiences. Fable has not experienced the transformation of China into a dominant global economic and political power, so it has no reason to try to better understand past moments where China was the dominant Eurasian economy and political power. It could help with any of these questions, and if I prompted it to come up with questions grounded in our current context, it might come up with a similar list. But it has no particular need to understand history and would be just as willing to walk you through a deep dive into string theory or MLB rules.

All of this creates a real problem for our public debates. The frontier systems sit behind expensive subscriptions and steep learning curves, so colleagues who have taken a principled stance against using AI have no easy way to know the scale of what changed this year. Informed refusal has become genuinely difficult, and that is a structural problem with how this technology is being deployed. Good-faith dialogue with people who are critically engaging with these systems is now the best way for those who refuse them to stay informed about what the technology can actually do. Refusers need honest reports from inside the tools, including the failures (LLMs can still fail at the edge of human knowledge; that is the topic for a future blog post). They, in turn, continue to do important work in our universities, pushing back against the uncritical and poorly thought out widespread adoption of these systems. That dialogue only works if both sides stay in the conversation.

AI disclosure: I wrote this piece and used Claude to copy edit (I’m very dyslexic and modern LLMs are transformative for people with language-based learning disabilities). I also used Claude for an adversarial review. I have an enterprise subscription from the University of Saskatchewan. I have no relationship with Anthropic.

Jim Clifford is a Professor of History at the University of Saskatchewan. His research focuses on urban Britain, global commodities, environment and heath. He is a co-editor of Historical Methods: A Journal of Quantitative and Interdisciplinary.

Since publishing my first book in 2024, I’ve turned my attention to gathering material for a second. Provisionally titled A View from the North: Lost Anglo-American Literature on Mexico from the Twentieth Century, I am exploring pulp novels, young adult adventure stories, tales of espionage, tourist guides, and yes, even postcards — in hopes of showing the extent to which the “Good Neighbor” cultural diplomacy of the twentieth century was, in fact, a genuinely intercultural endeavor between the United States and Latin America. Who were the small players — dime store novelists, postcard photographers, and nightclub owners — who got swept up in the large-scale international initiatives between North and South?

The Doris Z. Stone Latin American Library on the campus of Tulane University is an ideal place to examine this particular historical moment. The collection is replete with Mexico travel and tourism ephemera — magazines, hotel brochures, and highway maps — all of which, I believe, serve to better understand how our southern neighboring countries were constructed as attractive vacation destinations during the mid-twentieth century. Mexico especially loomed large in the imagination of US tourists; it was the period when, as historian Mauricio Tenorio shows, Mexico was understood as a “Brown Atlantis” — where revolutionary thought fermented and the Pan-American Highway promised access to exotic adventures. Everyone wanted to meet Frida Kahlo, everyone wanted to visit Teotihuacán, all while dreaming up global politics anew.

Two brochures found in the Mexican ephemera collection tell how Mexico feted itself for an international community.

Panoramic of the city center of Taxco de Alarcón, Guerrero, Mexico. Viewed from the Christ Monument looking southeast, via Wikimedia Commons.

First, is a trifold brochure from arguably Mexico’s most famous nightclub during the second half of the twentieth century — Cantarranas, located in the silver-mining town of Taxco, some two and a half hours outside of Mexico City. As the brochure details, the “Hacienda Cantarranas was built in 1538 by order of Hernán Cortés. The actual construction was done by his son Martin de Cortés.” The estate was used for silver processing. The locale, built with large stones on a hillside, became a nightclub in 1957 under the direction of entrepreneur Antonio “Tony” Reyes Ramírez. He would later become Taxco’s minister of tourism. Cantarranas was known worldwide for its revelry through the 60s and 70s before being acquired by the government of the Mexican state Guerrero in 1983, when it was converted into a culinary school and arts center. In 1992, it was turned over to the Universidad Nacional Autónoma de México as a school for foreign nationals. The hacienda was named “Cantarranas” — that is, literally “singing frogs” due to the loud chorus of frogs living in the area nearby. The brochure obviously plays upon this idea — even if not representative of the real spectacles of the club, the image is fetching.  

The brochure promises tourists that a night spent at Cantarranas includes “flamenco dancing by Estela Calderón,” “Carl Brice directly from Nassau, Bahamas,” “Primitive African Drums by the owner and Manager of Cantarranas Tony Reyes,” and “The Latin American Rhythms of the great pianist Juan García Esquivel.” The nightclub also housed distinct spaces — the “Twilight Room,” the “Patio,” the “Flamenco Room” and the “Mulata Room.” A newspaper article from 1974 also lists the club’s attractions, including “Flying Indian Men,” a discotheque called “The Psychedelic Cave,” bullfight lessons, a piñata party, and calypso songs by Carl Brice. By 1978, another newspaper reports that “Cantarranas is a little rough around the edges.” In 1980, Cantarranas had seemingly lost its sheen, as a newspaper article sarcastically notes “Cantarranas is the kind of place that you wouldn’t miss if you missed it. But worth it if you’re utterly bored.”

Cantarranas Nightclub Brochure. Courtesy of the Doris Z. Stone Collection at Tulane University.

Gone was the moment of Mexico’s mid-twentieth century Miracle. During the 1960s, newspapers still reported how, inside Cantarranas, “the audience moves en masse from room to room as each show finishes.” The brochure from Tulane explains that “among all the night clubs in Mexico Cantarranas was chosen for the filming of an episode of the N.B.C. colour T.V. Series ‘I Spy.’” That part of the brochure isn’t an exaggeration. The club was featured on the February 23, 1966 episode “Return to Glory.” Bill Cosby, playing the part of Alexander Scott — one half of a spy duo — is tipped off by US Intelligence to visit the club specifically, where he rendezvouses with the wife of a deposed president of an unnamed Latin American country. Famed Mexican actress Dolores del Río plays the part of the wife, as Bill Cosby and Robert Culp try to negotiate the democratic leader’s return to his home nation.

At least one similar brochure can be found online.

Surprisingly, the Tulane collection includes one more brochure with a singing frog on it — this one from Pemex or Petróleos Mexicanos, the company formed in 1938 by the Mexican government to sell the nation’s significant oil supply. The brochure includes maps of Mexican highways and invites travelers to explore the best routes. There is no mention of Cantarranas, or Taxco, or even nightclubs. Somehow, a singing frog had become emblematic of sightseeing around Mexico — the exotic sights, the electric nights, the cultural spectacles.

PEMEX Travel Club. Courtesy of the Doris Z. Stone Collection at Tulane University.

Intriguingly, in the decade that saw the beginning of Cantarranas’ end, a Mexican restaurateur — Carlos Anderson — opened in Mazatlán, Mexico the first restaurant of many that he would christen Señor Frog’s. The original locale, opened in 1971, tried to revive some of Cantarranas’ mid-twentieth century swagger, with waiters slinging tequila shots and cajoling spontaneous conga lines in a neon cave.

Thus, Tony Reyes’ “Singing Frogs” bar presaged today’s franchised “Señor Frog’s.” The brochure from Tulane documents how tourists were meant to imagine the delights of mid-twentieth century Mexico — strange, inviting, and culturally savvy — like a crooning amphibian. The Cantarranas and Pemex brochures ultimately serve to illustrate the extent to which commercial ephemera did the work that state pageantry once did. They are a testament to how compelling the “soft power” of the state was during the midcentury, when “Good Neighbor” diplomacy was translated into something a tourist could hold in their hand.

Further Reading

Linda Egan and Mary K. Long, eds., Mexico Reading the United States (Nashville: Vanderbilt University Press, 2009).

Dina Berger and Andrew Grant Wood, eds., Holiday in Mexico: Critical Reflections on Tourism and Tourist Encounters(Durham, NC: Duke University Press, 2010).

Douglas Monroy, The Borders Within: Encounters Between Mexico and the U.S. (Tucson: University of Arizona Press, 2008).

Darlene J. Sadlier, Americans All : Good Neighbor Cultural Diplomacy in World War II. (Austin, TX: University of Texas Press, 2012).

Stephen D. Morris, Gringolandia: Mexican Identity and Perceptions of the United States (Lanham, MD: Rowman & Littlefield, 2005).

W. Dirk Raat and Michael M. Brescia, Mexico and the United States: Ambivalent Vistas, 4th ed. (Athens: University of Georgia Press, 2010).

Dr. Kevin M. Anzzolin (Chicago, 1979), Lecturer of Spanish, arrived at Christopher Newport University in 2021, where he teaches a wide range of classes. His book, Guardians of Discourse: Literature and Journalism in Porfirian Mexico, was published with the University of Nebraska Press in May 2024 and garnered an Honorable Mention from LASA-Mexico for Best Book in the Humanities in 2025. His research focuses primarily on Mexican narrative from the 19th- to 21st centuries, and his work has been published in journals such as Letras Hispanas, Hispania, and Studies in Latin American Popular Culture. He is active in public scholarship as well, having written about pedagogy, pop culture, and local politics in different fora.E-mail: kevin.anzzolin@cnu.edu

In November 1926, Emma Goldman, then 57 and beginning a first period of exile in Toronto, enthused over a “radiant” young Italian woman seated at a welcoming dinner for Goldman organized by the city’s Jewish anarchist comrades.[1] Just over six months later, Goldman dubbed Marie Tiboldo “a terrible prude” who did “not feel anything deep enough, whether…for a man or ideas, to do anything worth while.” Tiboldo appears only fleetingly in Goldman’s estimated 200,000 letters, but her assessment of the young woman’s shortcomings aligns with Goldman’s pronounced tendency to go hot and cold with friends, comrades, and lovers. It’s not surprising, then, that Goldman also emphasized her continuing interest in “Marie,” writing that “I do not mean to give her up” and “I will certainly see much of her.”[2]

Marie Tiboldo (far right) at Bryn Mawr Summer School for Women Workers, 1929 (Julia Barnett Collection)

A Toronto-based protégé of Goldman’s (1869-1940) who outlived her “idol” by almost 70 years, Tiboldo (1904-2008) has remained virtually unknown even to Goldman specialists. Unlike some working-class women anarchists who, like Rose Pesotta, consciously fashioned their own archives, Tiboldo left behind no papers.[3] Goldman’s fame has often obscured the lives of other anarchist women but occasionally – as with Tiboldo – it has revealed clues about lesser-known figures in the period’s anarchist circuits.

Initial leads beyond Goldman’s letters were few but tantalizing, especially a short interview with a 99-year-old Tiboldo published in 2004 by Julia Barnett, a much younger socialist feminist who had befriended Tiboldo.  A US composer we met at a symposium marking the 150^th anniversary of Goldman’s birth led us to his brief 1993 videotaped interview with Tiboldo.[4] Research required attentiveness to inconsistences in the sources and the complex work of memory in the life of a long-lived Italian Canadian working-class anarchist. Our interest in Tiboldo stems from our project on how Goldman’s Toronto exile has been made and re-made inter-generationally in the city’s popular memory, with a focus on the political and cultural stakes of these reactivations.[5]   Tiboldo played a role in creating that memory, but her own story offers intriguing glimpses into the trajectory of Toronto anarchism.

Tiboldo was the US-born and Canadian-raised daughter of northern Italian anarchists who left the United States in 1914 for Toronto. Their radical networks in the city included an anarchist circolo in which Marie’s father, Lorenzo, was a driving force and the anarchist Branch 339 of the mainly Jewish (and socialist) Workmen’s Circle. The latter facilitated Goldman’s initial encounter with Tiboldo. As late as 1993, Tiboldo remained friends with Branch 339 co-founders, Morris and Becky Langbord.[6]  

A teenaged Tiboldo was hired in an embroidery shop in Toronto’s garment industry. She became a skilled embroidery worker and later designed embroideries for the “luxury trade,”[7] but exploitative conditions prompted worker unrest, leading to union activism and strikes. Led by socialists and Communists embedded in a vibrant Jewish working-class culture, garment workers, including women, became militants.[8]  Among the few young Italian women in the sweatshops, Tiboldo became a labour activist in this milieu, but the sources contain inconsistencies.

One narrative has Tiboldo single-handedly organizing her shop right after being hired in 1920. Consulting the Labour Gazette indicates instead that Tiboldo emerged as a rank-and-file organizer during a North American-wide organizing campaign launched in 1925 by the International Ladies Garment Workers Union (ILGWU).[9] A US-based international union affiliated with the American Federation of Labor, the ILGWU grew significantly in these years due in part to the militancy of young immigrant workers in New York City, many of them Jewish and Italian women. A union heavily shaped by anarchists and socialists, and a key site of working-class feminism, the ILGWU embraced a social unionism that heavily promoted workers’ education and culture and a “labor interracialism” that “elevated racial cooperation among the working classes as integral to a more egalitarian future.”[10]    

Tiboldo’s possible involvement in a successful 1926 strike by the Embroidery Workers Union, an affiliate of the ILGWU as Local 7 (Toronto), might explain her election not long afterwards as a delegate of that union to the Toronto Trades and Labour Council. And in 1929, she attended the Bryn Mawr Summer School for Women Workers, an immersive two-month program for industrial women workers that was also attended by Goldman comrade and anarchist labour organizer, Rose Pesotta.[11]

While Tiboldo had many male suitors, she neither married nor lived in a free love union. Influenced by Goldman’s radical views on sexuality and birth control, Tiboldo promoted young single women’s sexual autonomy, insisting they learn about sexual pleasure before marriage, not only the mechanics of pregnancy and giving birth.[12] Tiboldo praised the courage of the birth-control activists of her youth, though she likely knew that Goldman (among others) introduced Margaret Sanger to the birth-control cause, and then criticized her for abandoning radical politics for eugenics.[13] Proud of her association with Goldman’s famous April 1927 birth control lecture in Toronto, one that left a lasting impact on other left-wing women of the period,[14] Tiboldo critiqued the professionals, and their wives, who refused to chair the event. She recalled being horrified by Goldman’s suggestion that she chair it (thereby prompting Goldman’s ire) but agreed to be put “through some exercises” because it meant being with her “idol.”[15] Birth control activist Alice Loeb chaired the lecture.

Our forthcoming chapter on Tiboldo, which also covers her activism in the 1940s within the Communist-led United Electrical Radio and Machine Workers of America as well as her relationship with other Italian anarchists, offers further insights into the trajectory of working-class anarchism. Examining Tiboldo’s life on its own terms challenges any easy divide between sexuality-and-free-love rebels, of which Goldman is considered the exemplar, and anarchist labour organizers. Goldman’s own early history in the sweatshops is often ignored along with the material rhythms and conditions of her life as a revolutionary.[16] Goldman cultivated cross-class publics, but never lost ties with working-class anarchists for whom birth control and sexuality were fundamentally class issues and not external to class struggle. The Anarchist Queen could complain about her, but Tiboldo’s memories offer us valuable insights both into Goldman’s Toronto exile and the political choices made by Toronto’s anarchists before and after Goldman’s death in 1940.[17]  

Franca Iacovetta is a Toronto-based historian and a member of the riseupfeministarchive.ca collective.

Cynthia Wright teaches in the School of Gender, Sexuality and Women’s Studies, York University, Toronto/Tkaronto.

Today (August 21, 2026) marks the 133^rd anniversary of Emma Goldman’s famous Union Square, New York City “take bread” speech.

[1] Cited in Theresa Moritz and Albert Moritz, The World’s Most Dangerous Woman: A New Biography of Emma Goldman [hereafter WMDW] (Vancouver: Subway Books, 2001), 54.

[2] Emma Goldman Papers Public History Project, Emma Goldman to Ben Capes, 13 June 1927.

[3] Maria Tamboukou, “Labour Activists’ Archival Assemblages and Resistability in Memory Work: Emma Goldman, Jean Désirée, and Rose Pesotta,” Labour History 129 (November 2025): 29.

[4] Julia Barnett, “The Life and Times of Marie Tiboldo” [Barnett, “MT”]; New Socialist 46 (2004): 20-21; Interview with Tibaldo (sic) by Leonard Lehrman [LL interview with MT], Toronto, 1993, posted 2019, https://www.youtube.com/watch?v=t0BWLXGc3F4. Also, Minerva Davis, The Wretched of the Earth – And Me (Toronto: Lugus Publications, 1992), 83-6; Coleman Romalis, Emma Goldman – The anarchist guest (Documentary) 2000.  

[5] Currently entitled Remembering Emma Goldman in Toronto:  Making Intergenerational Radical Memory.

[6] ancestry.com Marie Tiboldo; Barnett, “MT”; LL interview with MT.

[7] Davis, Wretched, 88-9; LL interview with MT.

[8] Ruth Frager, Sweatshop Strife: Class, Gender, and Ethnicity in the Jewish Labour Movement of Toronto, 1900-1939 (Toronto: University of Toronto Press, 1992), chs. 5-7.

[9] Barnett, “MT”; Davis, Wretched, 88-9; Labour Gazette, April 1926, 397.

[10] Quotation from Victoria W. Wolcott, “Networks of Resistance: Floria Pinkney and Labor Interracialism in Interwar America,” Journal of African American History (Fall 2020): 569;  Annelise Orleck, Common Sense and a Little Fire: Women and Working-Class Politics in the United States, 1900–1965 (Chapel Hill: University of North Carolina Press, 1995); Jennifer Guglielmo, Living the Revolution: Italian Women’s Resistance and Radicalism in New York City, 1880–1945 (Chapel Hill: University North Carolina Press, 2010); Daniel Katz, All Together Different: Yiddish Socialists, Garment Workers and the Labor Roots of Multiculturalism (NYC: NYU Press, 2011).

[11] “Workers Are on Strike After Union Is Formed,” 5 February 1926 and “Workers Back on the Job,” 9 February 1926, Toronto Daily Star; Labour Gazette, April 1926, 387, 397; Tiboldo at Bryn Mawr, Globe and Mail, 3 August 1929; 1985 documentary, The Women of Summer : Bauman, Suzanne.

[12] LL interview with MT; Barnett, “MT.”  

[13] Candace Falk, Love, Anarchy, and Emma Goldman (New York: Holt, Rinehart, and Winston, 1984), 222-54.

[14] Dorothy Livesay, Journey with My Selves: A Memoir, 1909-1963 (Douglas and McIntyre, 1991), 66.

[15] Barnett, “MT”; LL interview with MT; Moritz and Moritz, WMDW, 86-8.

[16] Tamboukou, “Labour Activists,” 15.

[17] Cynthia Wright and Franca Iacovetta, “Radiant Creature and Anarchist Queen: When Marie Tiboldo Met Emma Goldman,” in Catherine Carstairs, Kassandra Luciuk, and Nadia Jones-Gailani eds. Feminist Provocations: Gender, Migration, and Activist Histories (University of Toronto Press, forthcoming).