SYNTACTIC PECULIARITIES IN CONSTRUCTING THE REALITY OF MARGARET ATWOOD’S THE HANDMAID’S TALE AND THE TESTAMENTS
Bibliographic record
Abstract
Margaret Atwood, a prominent Canadian figure in culture and literature, is known for her exploration of language in her works.This article examines how Atwood employs syntactic stylistic means in her dystopian speculative and science fiction novels, such as The Handmaid's Tale (1985) and its sequel, The Testaments (2019).The author delves into the dystopian aspects of totalitarian and consumer societies, employing a wide range of storytelling techniques.The article highlights the insufficient exploration of syntactic structures as crucial components in portraying dystopian worlds in Atwood's works.While foreign and Ukrainian scholars have extensively studied genre peculiarities, stylistic elements, and formal features in her novels, the examination of syntactic techniques remains understudied.By analysing the use of newly coined words and language in dystopian narratives, the article argues that language in these societies has become simplified and standardised, reflecting the stringent control of the ruling authority.It also explores how syntactic techniques enable Atwood to depict the marginalised voices and experiences of subjugated individuals.The article emphasises Atwood's effective use of language in capturing the characters' fear, desperation, and powerlessness.It analyses her employment of parcellation, aposiopesis, ellipsis, nominative sentences, parallel constructions, repetitions, and rhetorical questions to convey the characters' emotions and resistance against the oppressive regimes.Furthermore, the article compares the language patterns of different female protagonists in The Handmaid's Tale and The Testaments to reveal common elements such as defensive strategies, guilt, and mental struggles.It also explores the role of repetitive elements, such as epizeuxis, in highlighting the manipulation and indoctrination of characters within dystopian societies.Overall, this article provides an insightful examination of Margaret Atwood's use of syntactic stylistic means to shape the creation of her imagined dystopian worlds.It contributes to the understanding of her narrative techniques and the portrayal of power dynamics, oppression, resistance, and the struggle for freedom within these societies.
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 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.026 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".