Bibliographic record
Abstract
Anglo-Saxon(ist) Pasts, postSaxon Futures traces the integral role that colonialism and racism play in the field formerly known as Anglo-Saxon studies by tracking the development of the “Anglo-Saxonist,” an overtly racialized term that describes a person whose affinities point towards white nationalism. That scholars continue to call themselves “Anglo-Saxonists,” despite urgent calls to combat racism within the field, suggests that this term is much more than just a professional appellative. It is, this book argues, a ghost in the machine of early medieval studies—a spectral figure created by a group of nineteenth-century historians, archaeologists, and philologists responsible for not only framing the interdisciplinary field of "Anglo-Saxon" studies but for also encoding ideologies of British colonialism and Anglo-American racism within the field’s methods and pedagogies.Anglo-Saxon(ist) pasts, postSaxon Futures is at once a historiography of Anglo-Saxon studies, a mourning of its Anglo-Saxonist “fathers,” and an exorcism of the colonial-racial ghosts that lurk within the field’s scholarly methods and pedagogies. Part intellectual history, part grief work, this book leverages the genres of literary criticism, auto-ethnography, and creative nonfiction in order to confront Anglo-Saxonist pasts in order to imagine speculative postSaxon futures inclusive of voices and bodies heretofore excluded from the field formerly known as Anglo-Saxon studies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.012 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".