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Record W3116287972 · doi:10.1017/9781787449411.009

Robin Hood and Criminality

2020· other· en· W3116287972 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typeother
Languageen
FieldArts and Humanities
TopicShakespeare, Adaptation, and Literary Criticism
Canadian institutionsnot available
Fundersnot available
KeywordsCriminologySociology

Abstract

fetched live from OpenAlex

In contemporary popular imagination the legendary outlaw Robin Hood is often associated with opposition to the forest laws of the Anglo- Norman and then Plantagenet monarchs who ruled England from 1066 onwards, and it is sometimes assumed that his outlawry arose from his offences against those laws. There is, however, a growing consensus among both historians and literary scholars that the original Robin Hood, if one existed, had nothing to do with the forest laws or the greenwood, but was a notorious highway robber whose supposed association with forests and woodland came about only after the genesis of his legend. According to Barrie Dobson and John Taylor, by a now familiar paradox the genesis of the most famous forest outlaw in English literature seems to lie in the exploits of “a strong thefe” of Barnsdale who may not even have been an outlaw and who apparently had little connection with a forest in any sense of that ambiguous word … on the central question of how, and above all, when the highwayman of Barnsdale was transformed into an untransmutable forest outlaw the available evidence continues to remain obstinately imprecise. Later, when discussing the significance of the first appearance of the surname ‘Robehod’ in 1262, the pair thought that ‘a forest myth perhaps also engaged with the earliest associations which gathered round the name. There is no evidence that when first used the name Robin Hood had any greenwood associations. By some process that name was placed against a forest background’. According to Stephen Knight, the idea of his opposition to the forest laws as the reason for his outlaw status only became firmly established in novels, with the influential Robin Hood and his Men of the Greenwood , by Henry Gilbert, published in 1912, being of particular significance in that respect. Knight also pointed out that, because the criminality of killing deer contrary to the forest law does not appear in specific incidents in the medieval or later tales, episodes depicting it were only finally added to the legend in new Robin Hood stories devised for twentieth-century cinema, perhaps crucially in the 1938 film starring Errol Flynn, because the setting seemed to require it.

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)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.055
Threshold uncertainty score0.109

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.019
Scholarly communication0.0050.003
Open science0.0010.004
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.048
GPT teacher head0.231
Teacher spread0.183 · 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
GenreOther

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

Citations0
Published2020
Admission routes1
Has abstractyes

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