Jennifer Neville, <i>Truth is Trickiest: The Case for Ambiguity in the</i> Exeter Book <i>Riddles.</i> Toronto: University of Toronto Press, 2024, 376 pp.
Bibliographic record
Abstract
As the title indicates, this study focuses on the Old English riddles of the Exeter Book , with a particular emphasis on the ambiguity one faces when approaching these texts. The 95 riddles of the Exeter Book differ from the Anglo-Latin riddling tradition, out of which they emerged, in that they are unaccompanied by written answers. Jennifer Neville sees in this an advantage, rather than a limitation. She suggests that this lack of explicit solutions creates a different riddling experience, in which the goal was not the methodical finding of a definite solution, but rather the enjoyment of sustained thought and debate across a range of possible answers. Neville demonstrates the value of this approach throughout her book, with a particular emphasis on the ways that these riddles use various tropes to inform, trick, or mislead their readership.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".