Guests – Strangers – Aliens – Enemies: Introducing Ambiguities of Hospitality in the Middle Ages, c. 1000–1350
Bibliographic record
Abstract
Killing Guests: From Troy to DenmarkMany of our oldest stories are about killing guests.The thousand ships of Homer's Iliad set out to gain vengeance against Paris, who had abducted Helen, the wife of his host Menelaus.The cycle of killing that follows does not stop until, many years later, one of the avengers, Odysseus, returns home to kill his own overbearing guests, the suitors who had been attempting to woo his wife, Penelope. 1 The story of the massacre of the suitors and the servant girls who had had relations with them has rightly troubled scholars: Harry L. Levy saw it as fundamentally alien to the aristocratic ethos of the rest of the Odyssey and proposed it was an inherited tradition from a more parsimonious peasant tradition.For these, hypothetical, practically-minded country folk it was a crime worth killing for to waste the host's resources.But no such deconstruction is necessary: the ambiguity of hospitality, the obligations of guest and host, and the outcome of their interactions constitute a central narrative focus in the Odyssey.Odysseus himself is no perfect guest.He and his men predate the home of the cyclops Polyphemus, before themselves becoming the prey of their monstrous host.For his assault on Polyphemus, Odysseus earns the wrath of Poseidon, bringing destruction not only on himself but also his future hosts, before finally arriving at Ithaca.The clash between Odysseus and Polyphemus uncannily foreshadows the destruction 1 Reece, The Stranger's Welcome.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.026 | 0.023 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".