Men and Trolls: A Discussion of Race and the Depiction of the Sámi in the Hrafnistumannasögur
Bibliographic record
Abstract
This article discusses the often stereotyped and essentialized depiction of the Sámi in Old Norse sources in light of recent work on critical race theory and its application to the Middle Ages. Focussing on the portrayal of Sámi characters in the late-medieval Hrafnistumannasögur (Sagas of the Men of Hrafnista), this article argues that Norse portrayals of the Sámi were racial in character and that there did indeed exist a racial dynamic between the two peoples, at least during the late-medieval period from which these sagas survive. Consideration is also given towards how both positive and negative portrayals of the Sàmi in these sources can be understood within a racialized context. This article is a winner of the 2022 Marna Feldt Graduate Publication Award. À la lumière des récents travaux sur la théorie raciale critique [critical race theory] et son application dans le contexte du Moyen- ge, cet article traite de la représentation, souvent stéréotypée et essentialiste, des Samis dans les sources en vieux norois. Se concentrant sur les portraits des personnages Samis dans les Hrafnistumannasögur (sagas des hommes de Hrafnista) du bas Moyen- ge, cet article argumente que les représentations nordiques des Samis étaient de caractère racial et qu’il existait en effet une dynamique raciale entre les deux peuples, tout du moins durant le bas Moyen- ge, période d’où ces sagas nous proviennent. L’interprétation, dans un contexte racialisé, des représentations positives et négatives des Samis dans ces sources est également pris en considération. Cet article a reçu le Prix Marna Feldt de publication pour diplômé [graduate] de 2022.
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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 | 0.009 | 0.008 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".