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Record W2333773979 · doi:10.14288/1.0106058

The Tristram legend and its treatment by three Victorian poets: Matthew Arnold, Alfred, Lord Tennyson and Algernon Charles Swinburne

2012· article· en· W2333773979 on OpenAlexaff
Gwyneth McArravy Westwick

Bibliographic record

VenuecIRcle (University of British Columbia) · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicFolklore, Mythology, and Literature Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsLegendArtArt history

Abstract

fetched live from OpenAlex

In its earliest form, the Tristram legend was probably a Celtic folk-tale known in oral tradition as early as the eighth or ninth century. During the early part of the twelfth century it became known in France and Brittany; and there, in the later years of that same century, it was recorded in a lost romance now referred to as the Ur-Tristan. From this source, so it is believed, the earliest extant romances upon the subject were derived. During the twelfth century, two main versions developed—first the version des jongleurs, given in the poems of Béroul and Eilhart von Oberge, and second, the version courtoise given in Thomas's Tristan and some derivatives of it. Among these last, the Tristan of Gottfried von Strassburg, written about 1215, is generally regarded as one of the masterpieces of medieval literature. In the early thirteenth century, the legend was employed in an anonymous romance, the French prose Tristan. In this version, which was greatly influenced by the prose Lancelot cycle, the narrative is so grossly adulterated by the machinery of thirteenth-century courtly romance that the original love story is all but obscured. In most texts of the prose Tristan, even the traditional love-death scene is altered. This account of the legend became for five centuries the only version in which it was known. Two treatments of the legend appeared in Middle English literature. First is the northern Sir Tristrem, an anonymous poem composed about 1300 and based upon the Tristan of Thomas. Secondly, the Morte d'Arthur, composed by Sir Thomas Malory about 1469, contains an account of the Tristram legend based entirely upon the French prose Tristan. The legend did not again receive a major treatment in English literature until the mid-nineteenth century, when it became the subject of poems by Matthew Arnold, Alfred Lord Tennyson, and Algernon Charles Swinburne. Arnold's "Tristram and Iseult" is based, except for the love-death episode, upon the version courtoise. Arnold regarded as the central problem of the narrative, not the love story itself, but Tristram's conflicting loyalties to the two Iseults, and sympathized, not with the ill-fated lovers, but with Iseult of Brittany, the innocent victim of the tragic love. She becomes in his poem symbolic of the Stoic way of life, the compromise which Arnold offered to resolve the conflict of emotion and intellect. Tennyson treated the Tristram legend in "The Last Tournament," one of the Idylls of the King based upon Malory's Morte d'Arthur. The legend is employed in the moral allegory of the Idylls as an illustration of the evil consequences of adultery. In thus regarding the love story merely as a tale of adultery, Tennyson deviated greatly from the traditionally sympathetic treatment of the narrative. Swinburne's Tristram of Lyonesse is, like Arnold's poem, based chiefly upon the version courtoise. In Swinburne’s treatment the love story is again central, the theme being an exaltation of the ennobling and sanctifying power of human love. Along with the explicit exaltation of passionate love is an implied criticism of the hypocritical morality and distrust of passion which Swinburne regarded as prevalent in his age. Although these three Victorian poems differ widely in plot, characterization and purpose, the Tristram legend is employed didactically in each, and the purposes governing its didactic treatment are dictated by the age in which and for which the poems were written.

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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 score0.088
Threshold uncertainty score0.175

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.006
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.013
GPT teacher head0.180
Teacher spread0.167 · 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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Citations0
Published2012
Admission routes1
Has abstractyes

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