Bibliographic record
Abstract
Brian Stock's definition of textual community describes the process by which—in the face of growing levels of literacy and the rise of heretical movements in eleventh- and twelfth-century France—religious communities (from heretical sects to orthodox monastic communities) came to understand their identities through the mediation of written texts, which often were interpreted for them by key individuals. The text, the written word, became central to communal identity, affecting even the non-literate through its dissemination and acceptance by the members of the community. The relationship between the oral and the written, and the relationship developed between text and life, word and deed, in the interpretive models that developed out of texts and came to be applied to the lives of the readers or auditors, are two areas which are not the exclusive preserve of eleventh- and twelfth-century France, but are continuing concerns throughout the Middle Ages. Furthermore, the tendency to develop textual communities can also be found in the later medieval period, but with a different perspective on the question of literacy. For women religious in late-medieval England, for example, literacy usually did not denote Latinity but rather vernacularity; as a result, vernacular texts comprised the means by which these female religious came to understand their communal identity. While Bernard of Clairvaux's sermons on the Song of Songs addressed his male monastic community in Latin, women's religious rules formed a different kind of textual community that relied not on Latin exposition of mystical experience but on vernacular instruction concerning certain daily activities and proper conduct. The parallels between Stock's examples and the situation of medieval English female religious are still useful, because both highlight literacy, textuality, ritual, and activity as central to how communities define themselves.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.012 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".