Exploring the Journey of Self Identity and Women Empowerment in Patriarchal Society in Lucy Maud Montgomery’s Anne of Green Gables
Bibliographic record
Abstract
Lucy Maud Montgomery was born on November 30, 1874, in New London. She was a Canadian novelist, short story writer, and poet. One of her best novels, Anne of Green Gables, was a huge success. In this novel, Anne Shirley, an 11-year-old girl, is mistakenly sent to live with Marilla and Matthew Cuthbert, siblings who have planned to adopt a boy to help them with their farm, made up of the Canadian community of Avonlea. As she negotiates the difficulties of growing up in a patriarchal environment, the novel explores Anne’s journey of discovery as she navigates the challenges of growing up in a patriarchal society. This novel examines the interplay of communication theories within L.M. Montgomery’s Anne of Green Gables, focusing on how Anne Shirley’s journey reflects concepts such as interpersonal communication, identity negotiation, and self-presentation. The narrative highlights how Anne’s rhetorical skills and ability to adapt her language foster connections and overcome societal barriers. By bridging the thematic elements of belonging, empowerment, and identity with communication theories, this study explores the broader implications of language in shaping relationships and self-perception in the Avonlea Community.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.032 | 0.037 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".