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Record W2900403646 · doi:10.7311/0860-5734.27.3.06

Happy is the Land that Needs No Heroes

2018· article· en· W2900403646 on OpenAlexaffabout
Donna Coates

Bibliographic record

VenueAnglica An International Journal of English Studies · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsVictoryConvictIdentity (music)HistoryNational identityGender studiesSociologyLawMedia studiesPolitical sciencePoliticsAestheticsArt

Abstract

fetched live from OpenAlex

This essay interrogates two articles by the Canadian historian Jeff Keshen and the Australian historian Mark Sheftall, which assert that the representations of soldiers in the First World War (Anzacs in Australia, members of the Canadian Expeditionary Forces, the CEF), are comparable. I argue, however, that in reaching their conclusions, these historians have either overlooked or insufficiently considered a number of crucial factors, such as the influence the Australian historian/war correspondent C. E. W. Bean had on the reception of Anzacs, whom he venerated and turned into larger-than-life men who liked fighting and were good at it; the significance of the “convict stain” in Australia; and the omission of women writers’ contributions to the “getting of nationhood” in each country. It further addresses why Canadians have not embraced Vimy (a military victory) as their defining moment in the same way as Australians celebrate the landing at Anzac Cove (a military disaster), from which they continue to derive their sense of national identity. In essence, this essay advances that differences between the two nations’ representations of soldiers far outweigh any similarities.

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)0.002
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.383
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.034
GPT teacher head0.315
Teacher spread0.281 · 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

Citations2
Published2018
Admission routes2
Has abstractyes

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