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Record W3155416359 · doi:10.2478/stap-2020-0021

Permutations of Remembrance and (Counter-) Monumentalization: John Mccrae’s<i>in Flanders Fields</i>

2020· article· en· W3155416359 on OpenAlexaboutno aff
Anna Branach‐Kallas

Bibliographic record

VenueStudia Anglica Posnaniensia · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
FundersNarodowa Agencja Wymiany Akademickiej
KeywordsPoetryDecorumSociologyLiteratureCultural memoryCultural historyHistoryAnthropologyArt

Abstract

fetched live from OpenAlex

Abstract The article engages with the cultural impact of John McCrae’s canonical poem “In Flanders Fields” (1915), and more specifically the permutations of cultural memory and heritage discourse inIn Flanders Fields: 100 Years: Writing on War, Loss and Remembrance, edited by Amanda Betts and published in 2015. It shows how thirteen Canadians explore the revolutionary role of the poem in Canadian collective and individual memory, as well as its omissions and misrepresentations. The article juxtaposes the cultural history of the poem with Wilfred Owen’s “Dulce et Decorum Est” and its contemporary transformations, also showing how selected essays in the collection bridge the First World War with other armed conflicts. Applying Ann Rigney’s terminology, the article approaches the poem as a textual monument, demonstrating how “In Flanders Fields” has evolved from the role of astabilizerin Canadian cultural memory, providing a cultural frame for later recollections, to that of acalibrator, becoming a benchmark for critical reflection on dominant memorial practices.

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)0.002
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: none
Teacher disagreement score0.098
Threshold uncertainty score0.410

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0260.032
Scholarly communication0.0090.003
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.015
GPT teacher head0.238
Teacher spread0.224 · 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
Published2020
Admission routes1
Has abstractyes

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