Bibliographic record
Abstract
Naomi Griffiths, a path-breaking scholar of Acadian history, has had a career shaped by both character and chance. Her “Life in History” traces an extraordinary set of circumstances that brought her from a childhood among British egalitarian pacifists to an undergraduate degree in the United Kingdom, across the Atlantic to graduate school in New Brunswick, and then to a groundbreaking career at Carleton University. It is a story initially shaped by childhood bullying due to a long-undiagnosed disability (myopia), which forced her to develop resilience that later proved extremely useful over the course of her career. More than anything else, Griffiths believes her life and career has been one of extremely good fortune and deeply enriched by the generosity of her friends, colleagues, mentors, the members of the Acadian community who have supported her work, and the excellent students she had the good fortune to teach. Her approach to scholarship has been shaped by recognizing the shared humanity that we have with the people whose lives in the past we study, and she draws our attention to the need to be aware of one’s own standpoint in the questions we ask and how we judge historical evidence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.016 | 0.034 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".