The Uncanny History and Unrepresentability of Subject formation in Margaret Atwood's The Handmaid's Tale
Bibliographic record
Abstract
The Uncanny whose presence at least refers back to Freud's 1919 essay of the same title has been reconsidered by critics in recent century. The uncanny is no more attributed merely to the realm of aesthetic or psychology as Freud attempted to explain. It is rather an interdisciplinary issue to discuss our modern anxieties such as migration, gender, history, etc. Margaret Atwood (1939- ) is a contemporary Canadian writer who has reconsidered history. What makes her different from other writers is the way she rereads history. This article is an attempt to study The Handmaid's Tale, her 1985 novel through the uncanny. In her novel, history is a narrative whose uncanny reading foregrounds the unrepresentable realities in relation to subject formation. Through the uncanny, history which has been taken for granted as a familiar, clear and unchangeable "fact" becomes a strange, ambiguous and alternate "sign". The theories of Sigmund Freud and Jean-François Lyotard are mainly consulted to delineate the uncanny and history and their tendency to foreground the unrepresentabilities of subject formation. In Atwood's novel, Language and memory function as two significant uncanny issues whose indecisive and abeyant nature shun any historical "fact" to actualize as a familiar, clear and unchangeable given. This in turn, keeps the reader incessantly in the state of indecision and ultimately renders the process of subject formation as unrepresentable.
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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 | 0.001 | 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 | 0.013 | 0.027 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".