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Vernacular Traditions: Exploring Anglo-Saxon Mentalities

2015· article· en· W2214453814 on OpenAlexaboutno aff
Michael Matto

Bibliographic record

VenueThe Journal of English and Germanic Philology · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicMedieval Literature and History
Canadian institutionsnot available
Fundersnot available
KeywordsVernacularPoeticsPoetryLiteratureSubjectivitySoulPeriod (music)HistoryAestheticsSociologyPhilosophyEpistemologyArt

Abstract

fetched live from OpenAlex

Abstract Two recent books on Anglo-Saxon ideas about psychology have variants of the word “tradition” in their titles and develop theoretical paradigms around that term: Leslie Lockett’s Anglo-Saxon Psychologies in the Vernacular and Latin Traditions (2011) and Britt Mize’s Traditional Subjectivities: The Old English Poetics of Mentality (2013), both from the University of Toronto Press.1 While not primarily about the nature of traditions,2 both books rely on that term to frame their discussions of the psychology of the self and of how subjectivity manifests within different fields of Anglo-Saxon culture. In the earlier of the two books, Lockett offers a comprehensive account of Anglo-Saxon philosophical and theological concerns with the relationship among body, mind, and soul. In doing so she elaborates a distinction between two psychological models (and their variations) that were influential and productive in the Anglo-Saxon period. Mize’s project is narrower and deeper: he argues that the definition of the Anglo-Saxon poetic tradition itself should include a thematic and formulaic preoccupation with mentality. To read these books side-by-side is to see two authors’ projects weaving in and out of one another’s areas of interest and, in doing so, illustrating how fruitful psychology and mentality in Anglo-Saxon England can be as research topics. At the same time, they remind us how difficult it is to perceive pre-Christian “traditional” attitudes—whether about poetic conventions or psychological ideas—in the relatively late manuscript evidence we have.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.867
Threshold uncertainty score0.226

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.106
GPT teacher head0.235
Teacher spread0.129 · 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 teacher head, 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
Published2015
Admission routes1
Has abstractyes

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