Bibliographic record
Abstract
In June 1988, I was walking toward the McGill university chapel in Montreal, holding the hands of my five-and eight-year-old daughters, Emily and Anna.My parents walked a few steps behind.John Bradbury, my first husband, had died several weeks earlier.As we walked toward the chapel I was approached by one of my university colleagues.Over John's six-month battle with stomach cancer, I had become accustomed to the discomfort with dying and death that characterize late-twentieth-century Western societies.I had also benefited from enormous support from friends and neighbours.But this was a colleague whom I did not know very well.He was clearly searching for the right words to express his condolences."I just wanted to tell you," he started, in French, "I just wanted to tell you," he continued, "how lucky you are to be a widow and not divorced."I gulped, thought how glad I was that my parents' French was not fluid enough for them to understand him, thanked him, and filed the story away.Over time it became a good tale for dinner table exchange, sometimes another way to ease the discomfort of those who discovered for the first time that I had lived through a husband's illness and death.I recount this here, not to embarrass that colleague, should he read the book and remember, but rather because it serves as a reminder of the similarities between the ways divorce dissolves family today as widowhood did more frequently in the past.It also underlines the differences between people's familiarity with death and widowhood in the nineteenth century, and the discomfort of the twentieth and twenty-first centuries.Little about having experienced a husband's death or having been a widow myself helps me to understand the lives of the women I follow here from their marriages through their widowhood to their own deaths.The temporal and cultural distance of close to two centuries is immense.The gap between
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.219 | 0.114 |
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".