Framing of Identity and Personal History through Multiperspective Narratives in Margaret Atwood’s The Blind Assassin
Bibliographic record
Abstract
: Margaret Atwood’s The Blind Assassin (2000) is an engagement in layers of shifting identities and their eventual unravelling. The novel is dominated by the character and voice of Iris Chase, an octogenarian who slowly and fumblingly presents to the reader the fragmented and complex personal history of her family. The novel becomes an exercise in historiography through Iris’s visitations to her and her sister Laura’s youth in order to explain their tenuous relationship which is achieved through three parallel sources: Iris’s own attempts at a memoir, journalistic documents and letters from the past, and excerpts from an infamous novel published forty years previously. My paper will explore the three narrative structures present in the novel, and attempt to understand the questions of authorship and writing, and their importance in building a historiographic narrative. It will try to examine the ways in which retrospective interventions into public history helps to counter and create identities which were hitherto repressed under social decorum. This paper will borrow from Linda Hutcheon’s writings of the postmodern metanarratives in order to compose a lucid understanding of what alternative historiography in literature can achieve, keeping at the centre Atwood’s novel.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.032 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.006 |
| 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".