Bibliographic record
Abstract
I can remember very vividly the sense of distance, foreignness, and envy that I had towards Quebec French -and, correspondingly, towards French-speaking Quebec -while growing up in Ottawa.In Ottawa in the 1950s and 1960s, French was both far and near; a familiar accent, but also an inaccessible otherness.In the spring of 1965, shortly after I had turned nineteen, I was walking into the National Gallery when a young man was coming out.He looked unquestionably and irredeemably English Canadian: tall, with blond sandy hair, horn-rimmed glasses, and a tweed jacket.But as he passed the security guard he stopped and exchanged a few words: not the crisp, European, t-crossed, i-dotted French of the classroom, but a nasal sibilant whine that sounded almost like bagpipes.To my ears, Quebec French sounded like an inaccessible verbal code: as earthy, rich, and appealing as Cockney, as cool and harshly musical as a Southern blues harmonica.And when I heard this unmistakable Anglo exchange a few words and a chuckle, words I could not separate from one another, let alone understand, I was struck with envy.That flash of envy, of desire to become someone who could speak that exotic other language, was at the root of my desire to go to Quebec and to come to terms with it.That summer, I worked on an archeological dig at Fort Lennox on the Richelieu River, south of Montreal, and began a process of infatuation and discovery that would ultimately result in this book.I was struck by the contrasts of Quebec in 1965: a society that, on the one hand, was bursting with nationalist energies and, on the other hand, was still plagued with insecurities and resentments.Similarly, I encountered two different English Montreals -one that I had known through my parents, and during summers as a child in the Eastern Townships: a gracious, greystone, tree-lined place, full of quiet streets and vii
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.606 | 0.429 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".