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Record W1585362669 · doi:10.26686/wgtn.16992901.v1

The Landscape of Empire:   the Place of Landscape in 19th Century Colonial Novels

2010· dissertation· en· W1585362669 on OpenAlexaboutno aff
Rebecca Leah Gordon

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicAustralian History and Society
Canadian institutionsnot available
Fundersnot available
KeywordsDepictionColonialismContext (archaeology)IndigenousEmpireHistoryLiteratureGeographyArtArchaeologyEcology

Abstract

fetched live from OpenAlex

This thesis presents a comparative research study of four novels published within two years of 1881 in four colonies of the Victorian Empire. The novels are Waitaruna: A Story of New Zealand Life by Alexander Bathgate from New Zealand, Gathered In by Catherine Spence from Australia, Neville Trueman: The Pioneer Preacher, a Tale of the War of 1812 by W. H. Withrow from Canada, and finally The Story of an African Farm by Olive Schreiner from South Africa. These novels were chosen because of their close publication dates. My purpose is to compare the depictions of landscape in each novel. The purpose of this study is to discover the depiction of landscape in the novels and the effect of the landscape on the characters. Because the authors were writing as English subjects in a non-English setting, they each had to engage differently with the landscape in their novel, depicting the settler experience of colonising the new country. Each novel’s portrayal of landscape is analysed using the text and placed into the historical context of the colony and the literary development of the colony. The findings of all four novels are compared to identify the differences and similarities discovered in the initial analysis. These final chapters show that landscape was closely tied with the settlers’ conceptions of religion, the treatment of the indigenous people, and settler experience in the particular colonies as represented by these authors. The importance of this thesis and the comparative study at the end is that my study gives an in depth analysis of four novels from four different colonies that have previously not been compared. The selection of the novels based solely on date of publication makes the comparison all the more interesting because these novels were not chosen due to their content, so the similarities and differences of the novels point out the similarities and differences of the authors’ literary portrayals of the colonies in a comparison study that has not yet been done.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0170.024
Scholarly communication0.0100.006
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.014
GPT teacher head0.300
Teacher spread0.286 · 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 designQualitative
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
Published2010
Admission routes1
Has abstractyes

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