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Record W7113616013

“I love things just as much as people”: Material Culture and L.M. Montgomery’s Emily Trilogy

2025· other· en· W7113616013 on OpenAlexaboutno aff

Bibliographic record

VenueDublin City University Open Access Institutional Repository (Dublin City University) · 2025
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsTrilogyReading (process)Focus (optics)Culture theoryCelebrity cultureClose readingIdeal (ethics)Intersection (aeronautics)Point (geometry)
DOInot available

Abstract

fetched live from OpenAlex

The intersection of material culture with children’s fiction is an underexplored area of study. Lucy Maud Montgomery, the Canadian author most famous for Anne of Green Gables, provides an ideal starting point for such an examination. Most of Montgomery’s twenty novels are categorized as children’s fiction and contain references to hundreds of everyday objects with varying degrees of significance: some hugely symbolic or plot-driving, others seemingly incidental but often with unexpected meaning. Montgomery represented her time and place in her realistic fiction and perhaps had no intention of drawing particular attention to material things. However, I argue that these objects are a significant aspect of her fictional worlds, connecting characters, propelling narratives, and enabling protagonists’ growth and development, as well as illuminating aspects of the culture and society of Canada in the early twentieth century. In applying material culture theory to Montgomery’s fiction, I am using various works to provide anthropological context, sources on children’s literature, and others on Montgomery studies to explore the roles of objects in these works with a particular focus on the Emily trilogy. Using close reading and the application of material culture theory as my methodologies, I examine the significance of objects to the protagonist’s growth as a young woman and her career development despite various barriers, as well as exploring connections between characters and even between author and reader.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Open science, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.520
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0060.005
Science and technology studies0.0030.002
Scholarly communication0.0030.010
Open science0.0100.011
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.029
GPT teacher head0.295
Teacher spread0.266 · 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; both teacher heads agree on what is shown here.

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
Published2025
Admission routes1
Has abstractyes

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