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From Lawmen to Plowmen: Anglo-Saxon Legal Tradition and the School of Langland

2017· article· en· W4249226148 on OpenAlexaboutno aff
Andrew Rabin

Bibliographic record

VenueThe Journal of English and Germanic Philology · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical Legal Studies and Society
Canadian institutionsnot available
Fundersnot available
KeywordsPhilologyIconCitationHistoryClassicsLibrary scienceArtPolitical scienceLawComputer science

Abstract

fetched live from OpenAlex

Book Review| April 01 2017 From Lawmen to Plowmen: Anglo-Saxon Legal Tradition and the School of Langland From Lawmen to Plowmen: Anglo-Saxon Legal Tradition and the School of Langland. By Stephen M. Yeager. Toronto Anglo-Saxon Series, 17. Toronto: Toronto University Press, 2014. Pp. x + 268. $65. Andrew Rabin Andrew Rabin University of Louisville Search for other works by this author on: This Site Google The Journal of English and Germanic Philology (2017) 116 (2): 228–230. https://doi.org/10.5406/jenglgermphil.116.2.0228 Cite Icon Cite Share Icon Share Facebook Twitter LinkedIn MailTo Permissions Search Site Citation Andrew Rabin; From Lawmen to Plowmen: Anglo-Saxon Legal Tradition and the School of Langland. The Journal of English and Germanic Philology 1 April 2017; 116 (2): 228–230. doi: https://doi.org/10.5406/jenglgermphil.116.2.0228 Download citation file: Zotero Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All Scholarly Publishing CollectiveUniversity of Illinois PressThe Journal of English and Germanic Philology Search Advanced Search The text of this article is only available as a PDF. Copyright 2017 by the Board of Trustees of the University of Illinois2017 Article PDF first page preview Close Modal You do not currently have access to this content.

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)0.002
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.031
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.005
Science and technology studies0.0010.002
Scholarly communication0.0040.004
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0310.006

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 head0.017
GPT teacher head0.273
Teacher spread0.256 · 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".

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Citations1
Published2017
Admission routes1
Has abstractyes

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