Review of <i>Trailblazers: The Lives and Times of Michael Ewanchukand Muriel (Smith) Ewanchuk.</i> By John Lehr and DavidMcDowell.
Bibliographic record
Abstract
Belonging to the genre of local history, Trailblazers explores the lives of two Canadians in the province of Manitoba spanning the 20th century. They were, as the introduction states, ordinary people, just like us. There is much here to interest the casual reader and the serious historian alike. Readers of Great Plains Research may need to be reminded that while the geographic designation "Great Plains" extends into the western Canadian provinces, the term is purely American. Canadians use the generic term "prairie." Michael Ewanchuk was a teacher, a principal, and finally a school inspector for 23 years; Muriel was a teacher whose professional career effectively ended in 1941 when she married, since married female teachers were not hireable in that era. In their introduction and conclusion, John Lehr and David McDowll effectively place the story of Michael and Muriel within the cultural and social milieu of their times. Issues of environment, colonialism, racism, and feminism are integrated into the narrative without ever being heavy-handed or overly academic.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".