“Health of the World”: The Symbolic Associations of Trees in Eleventh-Century England, in the Context of Landscape
Bibliographic record
Abstract
The Christianization of Anglo-Saxon England in the seventh century CE was a momentous period of religious change which had many far‐reaching effects. Anglo-Saxon paganism had attached a set of sacred and symbolic meanings to various natural features in the English landscape. In this belief system, trees and groves were strongly associated with healing and defensive powers. This paper will argue that due to the persistent presence of once-sacred trees and groves in the English landscape, combined with a continually widespread demand for health remedies, the pre-Christian associations of trees with healing and defense in England were not easily forgotten after the conversion period and in fact continued throughout the eleventh century. However, these pre-Christian symbolic associations were effectively subsumed within the hegemony of a Christian ideological framework. A continual, bidirectional alignment of these symbolic associations of trees with elements of Christian symbolism, namely that of Paradise and that of the Cross, served to explain and legitimize their syncretic continuation within this Christian framework. These insights invite us to appreciate some of the complexity of the syncretism that occurred during the period of Christian conversion in Anglo-‐Saxon England. They also invite us to further contemplate some of the lasting effects of this gradual syncretic process.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.028 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".