Bibliographic record
Abstract
Conversion is perhaps the dominant topic of Old English texts. Not only do many of the poems of Anglo-Saxon England represent large groups of heathens being converted to the Christian way of life, but they also encourage individual listeners and readers to turn back towards God after having fallen briefly away through sin. These two types of conversion, macro and micro, are similar in that they both involve a negating of all that is not Christian. Because that negation is gradual and always in need of being re-accomplished, Karl Morrison describes conversion as always being a work in progress, rather than an instantaneous transformation. Morrison argues that conversion is as much process as it is a moment of stupendous insight or absolute discovery. Rather, conversion—especially as it is represented in conversion narratives—involves constant reappraisal, and remains "part of a strategy for survival."' The macro-conversion, the instantaneous moment in which often an entire group converts, occurs in such Old English poems as Andreas, while the micro-conversion, the individual process of constant re-evaluation and re-conversion, occurs in poems such as Guthiac. The goal of both types of conversion is unity with God, an "empathetic participation in which the and 'you' bec[o]me one" (Morrison 85). This unity has two dimensions: a divine and mystical union with God and the secular and political unity of people into a Christian community. The process of both conversions involved a negotiation between Christian belief and doctrine, as embodied in biblical texts, and the application of that belief in the lives of individuals throughout what would later be called Christendom. The Anglo-Saxon use of vernacular poetry as one site of that negotiation offers an opportunity to investigate the ways in which prophetical traditions are transposed and recreated in one early medieval group of kingdoms.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.011 | 0.019 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".