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Record W4310368495 · doi:10.5539/res.v14n4p61

Livonian Werewolves: Assessing Their Historical Significance Through the Case of Old Thiess

2022· article· en· W4310368495 on OpenAlexvenueno aff
Jiaxin Liu

Bibliographic record

VenueReview of European Studies · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean Linguistics and Anthropology
Canadian institutionsnot available
Fundersnot available
KeywordsHappeningEliteContext (archaeology)Value (mathematics)Reading (process)MetaphorPeasantSociologyHistoryLawSocial scienceLiteratureEpistemologyPoliticsPolitical sciencePhilosophyArt historyArtPerformance artLinguistics

Abstract

fetched live from OpenAlex

This paper seeks to investigate the phenomenon of Livonian werewolves from the early modern era (1500-1700s). Noting their uniqueness in comparison to contemporaneous werewolves hailing from other geographic areas, the paper suggests that the Livonian werewolf is a metaphor for Livonian society at that time, one which was characterized by social turmoil and strict class hierarchy. This metaphor was utilized by different classes to establish their own interests in society, and thus the paper concludes that the werewolf is a mutable artifact whose value is contingent on its social context. This is demonstrated with the particular case of Old Thiess—a poor, elderly Livonian peasant who gave an unorthodox and anomalous testimony when accused of being a werewolf. In his court statement, it is shown how Thiess was in fact alluding to social tensions by lambasting the rich German elite and establishing the righteousness of the peasantry, of which he was a member of. A close reading method was utilized on the trial transcript of Old Thiess, translated from Hermann von Bruningk’s Der Werwolf in Livland. Through a contextual reading of Livonia’s social atmosphere, the paper draws connections between the content of the trial to wider societal disturbances happening at the time.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0080.014
Scholarly communication0.0040.003
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.122
GPT teacher head0.409
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

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