Giving an account of oneself: Tracing the Moravian Edwards family through six generations of Lebenslauf life writing
Bibliographic record
Abstract
One fundamental way to leave a mark in life is to write an account of oneself, whether as a memoir or an autobiographical sketch. For Moravians, this practice is a spiritual requirement and takes the form of a Lebenslauf, which translates to ‘life account’. The Edwards family, of which I am a descendant, has been Moravian for many generations and has lived in Moravian settlements across several countries, including England, Ireland, Canada and South Africa. Family records and archival searches have uncovered a number of Edwards’ Lebenslauf memoirs – both short and long, authored by men and women, and encompassing both autobiographical and biographical narratives. These works have appeared in church records, and some remain unpublished, intended to be passed down to family descendants. Contribution: This article aims to trace the development of the Moravian Church movement in the United Kingdom and South Africa through the life writings of the Edwards family across six generations. It will highlight the differences between the writings of men and women, as well as track the changes in social and religious norms experienced by those who lived through these periods, starting in 18th-century Europe and concluding in the 21st century with the South African Moravian descendants, who have since spread further afield.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.015 | 0.012 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".