Empowering the Subalterns: Margaret Atwood's Quest for Historical Voices in The Testament
Bibliographic record
Abstract
This article explores The Testaments by Margaret Atwood in light of Spivak’s postcolonial perspective based on her article “Can the Subalterns Speak?” such as “widow sacrifice” and “epistemic violence” to scrutinize the situation of the subaltern women in Gilead. What Atwood portrays in her novel mainly revolves around voiceless women who are silenced by the hegemony. First, it attempts to shed light on how the government of Gilead managed to keep subaltern women voiceless. Afterward, it highlights the potential benefits for a First World country like Canada in advocating the voices of marginalized Gileadeans, while also exploring the significance of amplifying those voices that may endure in history. Finally, it intends to show how Atwood managed to be the voice of the subaltern women by having formed her novel through gathering three narratives to tell their accounts of the story, in addition to an account that will be produced by future intellectuals on Gilead. It can be suggested that Atwood challenges the conventional process of shaping history through the dominant voices in power, exemplified by characters like Aunt Lydia and the Canadians, by including the perspectives of Agnes and Daisy in her novel.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.022 | 0.028 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.006 |
| 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".