Bibliographic record
Abstract
So, it was January the 18 and it was the middle of the night. And it was very, very cold. Snow was — we went just about knee deep in snow — And we went on the road going toward Posen, capital of Wartegau. And so we said, “Let’s take that direction.” Just going by the moon and the stars. (Katja Enns) Going by the Moon and the Stars tells the stories of two Russian Mennonite women who emigrated to Canada after fleeing from the Soviet Union during World War II. Based on ethnographic interviews with the author the women recount, in their own words, their memories of their wartime struggle and flight, their resettlement in Canada and their journey into old age. Above all, they tell of the overwhelming importance of religion in their lives. Through these remarkable stories Pamela Klassen challenges conventional understandings of religion. The women’s voices, intimate and powerful, testify to the importance of religion in the construction of personal history, as well as to its oppressive and liberating potential. Going by the Moon and the Stars will be of great value to all those interested in the Mennonites and Mennonite history, religion, women’s studies, ethnic studies and life history.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".