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Record W7054459163

Anne Shirley’s Characterization and Character Development as The Reflection of Her Imagination in Montgomery’s Anne of Green Gables

2014· dissertation· en· W7054459163 on OpenAlexaboutno aff

Bibliographic record

VenueUniversitas Airlangga Repository (Universitas Airlangga) · 2014
Typedissertation
Languageen
FieldEngineering
TopicLaser Design and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsCharacter (mathematics)Reading (process)CriticismReflection (computer programming)Character developmentCharacterization (materials science)GirlNarrative
DOInot available

Abstract

fetched live from OpenAlex

This thesis is presenting an analysis of major character in the novel written by Canadian author; Lucy Maud Montgomery, titled Anne of Green Gables. Anne Shirley – the major character – is portrayed as an imaginative girl in this novel. She was living in orphan asylum before being mistakenly adopted by unmarried siblings, Marilla and Matthew Cuthbert who lived in Green Gables. This thesis will analyze Anne Shirley’s characterization and also her character development as the reflection of her imagination. Therefore the aim of this thesis is to find about Anne Shirley’s characters and character development as the reflection of her imagination. New Criticism is the theory that will be use in this thesis and only focuses on the novel instead of the author’s intention. The data analysis is descriptive-qualitative and the method in data collecting is close reading from library researches whether it is from book or online. In finding Anne’s characterization, the foundation of characterization by Richard Cohen will be use and also the stages of character development in Child psychology by Lester D. Crow are use in finding Anne’s character developments. Along in finding Anne Shirley’s character, imagination becomes her main character. The writer also finds about Anne character development, that she gradually becomes very mature and can make her own decision when finally she chooses to stay in Avonlea rather than pursuing her scholarship. But she never gives up hope and keeps on studying even if she has to do it without study under one academy.

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 score0.057
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0060.010
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.185
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

Citations0
Published2014
Admission routes1
Has abstractyes

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