“DISTANCE LEARNING” IN THE NINTH CENTURY?: MICRO-CLUSTER ANALYSIS OF THE EPISTOLARY NETWORK OF ALCUIN AFTER 796
Bibliographic record
Abstract
Scholars of eighth- and ninth-century education have assumed that intellectuals did not write works of Scriptural interpretation until that intellectual had a firm foundation in the seven liberal arts.This ensured that anyone who embarked on work of Scriptural interpretation would have the required knowledge and methods to read and interpret Scripture correctly. The potential for theological error and the transmission of those errors was too great unless the interpreter had the requisite training. This dissertation employs computistical methods, specifically the techniques of social network mapping and cluster analysis, to study closely the correspondence of Alcuin, a late-eighth- and early-ninth-century scholar renowned for his pedagogy (which was rooted in the liberal arts) and his Scriptural commentaries. These methods allow us to identify and study these two types of knowledge and how Alcuin imparted them to individuals at two different stages of their respective intellectual careers. This investigation focuses particularly on the less-studied period of Alcuin’s life, his final eight years, beginning when he departed either the imperial court or a nearby school and arrived in Tours in 796, and ending with his death in 804.\nThe increase in Alcuin’s surviving letters after 796, and the ways in which Alcuin imparted knowledge to the recipients, many of whom were his former students, provides the basis for exploring how Alcuin used the only technology available to him, writing, to maintain his relationships and continue to impart knowledge and attempt to influence his former pupils. These letters further demonstrate the different stages and methods for education. While Alcuin used the physical classroom in Tours to teach the seven liberal arts, the study of exegesis took place among the well-trained aristocratic and intellectual elite, who had the ability to closely control the production and dissemination of the “correct” interpretation of Scripture.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".