Conceptions, Uses, and Transformations of Wetland Environments in England c.1000-1400
Bibliographic record
Abstract
This thesis examines coastal wetland landscapes, and human relations with them, in England c.1000-1400, specifically the Pevensey Levels in Sussex and Romney Marsh in Kent.It relies on hagiography, legends, poetry, medical writing, administrative documents, archaeology and chronicles to explore the ways in which medieval people conceived of and lived in wetlands.Thus it lies at the intersection of social, economic, medical, environmental and cultural history.I interrogate the ways in which medieval literary sources describe and understand wetland environments, explore how medical treatises understood wetlands in relation to a miasmatic understanding of contagious disease, (particularly malaria) and use archaeological sources as well as manorial and royal records to examine the economic, political, and agricultural uses of wetlands, particularly in the context of drainage.In the earliest period of the study, c.1000-1200, the wetland and the body are understood to be in dialogue with one another.People could change and impact their landscape, and in turn the landscape changed those who entered or dwelt within; in this way, people are intimately tied to their landscape.Malaria posed a challenge for wetland inhabitants, but it was debilitating rather than deadly for those who were born and raised in the marsh.The wetlands used as a case study here also provided resources, and both elites and common people were able to benefit from fishing, fowling, and foraging, pasturing and the production of salt.Relations with the swamp varied with social status, with the poor and landless relying most heavily on the landscape's resources.In this way, people of all social statuses were able to benefit from the wetland landscape, and those who lived within this environment were understood to be fundamentally connected to their environment.However, by the thirteenth century, attitudes shifted, with landlords draining the wetlands to add to their demesne.The impetus to "improve" the land continued and accelerated through me.I am also very grateful to Margot Mathieu, who got me through the worst days, made sure I took breaks, and worked side by side with me to help us manage our time; and to Jean-Philip Mathieu, for making Margot and me macaroni and cheese, talking through our respective dissertations, and giving feedback on my writing.Both of your friendship has been a lifesaver.And finally, I want to thank my husband, Christian Koehler.Your love, support, patience, and willingness to listen to me talk about swamps for the millionth time
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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 | 0.004 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".