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Record W7111873251

Landscapes of Survival: Transplant and Sustenace in Willa Cather's Canadian Writing and Experience

2011· article· en· W7111873251 on OpenAlexaboutno aff

Bibliographic record

VenuePortuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicAmerican and British Literature Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsTheme (computing)SustenanceImmigrationReading (process)Settlement (finance)BeautyCarvingLife writing
DOInot available

Abstract

fetched live from OpenAlex

As many critics have pointed out, Willa Cather’s main theme is the meeting of the intellectual and cultural inheritances of Europe and the ‘great fact’ of the settlement of the New World, whether in Nebraska, New Mexico or Quebec. Bearing in mind Margaret Atwood’s imagery of survival, I will try to show how these images relate to Cather’s pervasive theme of Old World immigrants carving out a place of beauty and salvation in the New World. Henceforth, I’ll attempt to expand on the motives which led Cather to see Canada, namely in Shadows on the Rock (1931), as a land of possibilities, a geography which responds to her characters’ need for redefining both their physical and interior borders. My reading of Cather’s Canadian writings and experience has met and enlightened several of the issues which define Canada’s culture: the meeting of the Old and New World, geography as the great fact of Canadian identity, and the multicultural composition of its social tissue. Moreover, Cather’s Canadian writings reiterate Canada as a country of possibilities, one which provides landscapes of survival for characters in search of sustenance and looking for new forms and visions.

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)0.004
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: Other · Consensus signal: Other
Teacher disagreement score0.074
Threshold uncertainty score0.534

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0530.041
Scholarly communication0.0120.004
Open science0.0020.004
Research integrity0.0040.007
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 head0.061
GPT teacher head0.323
Teacher spread0.262 · 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
Published2011
Admission routes1
Has abstractyes

Explore more

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