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Record W2795373574

Fact, Fiction, and the Tradition of Historical Narratives in Nineteenth-Century Canadian Children's Literature

2007· article· en· W2795373574 on OpenAlexaffabout
Elizabeth A. Galway

Bibliographic record

VenueCanadian Children's Literature / Littérature canadienne pour la jeunesse · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsPrideIdeologyPoetryNarrativeIdentity (music)HumanitiesNational identityHistoryEthnologyLiteratureArtPoliticsPolitical scienceAestheticsLaw
DOInot available

Abstract

fetched live from OpenAlex

Resume: Imbu de sa souverainete nouvellement acquise, le Canada anglais a utilise, vers la fin du dix-neuvieme siecle, la litterature pour la jeunesse comme un outil privilegie, afin de developper son identite nationale et de susciter l'adhesion des jeunes a ses valeurs culturelles. L'attention des auteurs s'est particulierement portee sur la production des œuvres a caractere historique, dont l'etude fait ressortir l'existence de tensions ideologiques et politiques au tournant du vingtieme siecle. Summary: During the late nineteenth century, as Canada came to terms with its new role as an independent nation, attempts were made to strengthen a sense of Canadian national pride and identity. In English-speaking Canada, children's literature was regarded as a means through which a strong identification with the new confederation could be achieved in the nation's youth. Writers were beginning to examine the events of Canada's past through historical textbooks, poems, songs, and novels. A study of these historical narratives for children reveals some of the ideological tensions that existed within Canada at the dawn of the twentieth century.

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)0.003
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: Empirical · Consensus signal: none
Teacher disagreement score0.188
Threshold uncertainty score0.941

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0070.010
Science and technology studies0.0370.041
Scholarly communication0.0140.003
Open science0.0020.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.000

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 head0.004
GPT teacher head0.184
Teacher spread0.180 · 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
Published2007
Admission routes2
Has abstractyes

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