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Record W3113022660 · doi:10.5817/bse2020-2-7

Tribute to Newfoundland, tribute to fatherland : Michael Crummey's Sweetland in a geocritical perspective

2020· article· en· W3113022660 on OpenAlexaboutno aff
Ewelina Feldman-Kołodziejuk

Bibliographic record

VenueBrno Studies in English · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTributePerspective (graphical)FatherlandEnvironmental ethicsSociologyArtArt historyPhilosophyPolitical scienceLawVisual artsPolitics

Abstract

fetched live from OpenAlex

The article invites a reading of Michael Crummey's Sweetland (2014) from the geocritical point of view.The novel is a fictional record of the resettlement of a fishing town situated on an imaginary island off the coast of Newfoundland.The main character refuses to leave his home, and by feigning his own death manages to stay behind when all other inhabitants depart.The proposed analysis employs such geocritical tools as geobiography, cartography, sensory experience of the land and its agency, regionalism as well as Pierre Nora's concept of lieu de mémoire.The article analyzes the geobiographical elements in the novel to underscore the book's status as Crummey's tribute to his fatherland.It investigates the factors that prevented the protagonist from taking the resettlement package and the transformations that the deserted island undergoes.It also elaborates on the motif of the map in the discussed narrative and reflects on the role of Newfoundland literature in preserving regional identity.

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)0.001
metaresearch head score (Gemma)0.002
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: Empirical
Teacher disagreement score0.364
Threshold uncertainty score0.732

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0190.018
Scholarly communication0.0070.002
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.070
GPT teacher head0.389
Teacher spread0.319 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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