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Record W7132948709

'Beauty, Garlanded in Hell': The Tenacity of Cultural Christianity in First World War Britain and Canada

2023· dissertation· en· W7132948709 on OpenAlexaboutno aff
Alana Alexandra Harton Morgan McCord

Bibliographic record

VenueTSpace · 2023
Typedissertation
Languageen
FieldSocial Sciences
TopicWorld Wars: History, Literature, and Impact
Canadian institutionsnot available
Fundersnot available
KeywordsChristianityFirst world warWorld War IIFraming (construction)ScholarshipTenacity (mineralogy)World view
DOInot available

Abstract

fetched live from OpenAlex

More than one hundred years after its conclusion, the collective trauma of the First World War is still felt by both individuals, and entire nations. During the war itself, and in the post-war world, there was a palpable desire to find meaning in the conflict, and in culturally Christian countries such as Britain and Canada, that culture was often used to frame the war experience. This framing was not solely dependent on personal belief or unbelief. Indeed, it was effectively employed both by individuals who questioned orthodox religious practices or resented figures of ecclesiastical authority, and those whose personal beliefs remained unshaken or who sought to maintain the status quo. First World War scholarship has traditionally dismissed the influence of religion on the war, but contemporary published and unpublished writings are indicative of the tenacity of the metaphors, tropes, and practices of a culturally Christian group of people, and these metaphors, tropes, and practices became a common idiom which allowed for greater communication between soldiers and civilians. In the same way, an examination of the use and impact of that cultural Christianity gives a far greater insight into the experiences of people during and after the war, than has previously been considered.

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)0.006
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 score0.105
Threshold uncertainty score0.765

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0340.033
Scholarly communication0.0120.002
Open science0.0020.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.000

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 head0.031
GPT teacher head0.351
Teacher spread0.320 · 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
Published2023
Admission routes1
Has abstractyes

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