Bibliographic record
Abstract
Silence is a concept both praised and criticised when put to practice. The latest trends in society encourage individuals to be their true selves; simultaneously, some are reproached for presenting too much of themselves to the world. In this sense, discretion is arguably closely linked to a performative silence used as a rhetorical tool for self-protection. The question is whether silence and performativity are opposite or complementary terms. The main purpose of this article is to analyse this binary logic from an intersectional perspective. More specifically, to ascertain whether resistance to society’s limitations can be performed through silence or necessarily through performative actions. The case study is Margaret Atwood’s novel Alias Grace (1996) set in mid-nineteenth century, puritan Canada. Atwood’s postmodern fictionalization of Grace Marks makes her a conflicted character with a duality that terrorises society. She is, in Hegelian terms, both the Master and the Slave. Grace’s discretion later becomes performative, in the sense that it alters reality and brings something new into existence: her social resistance. This article has led to the conclusion that Grace makes a calculated use of her silence in an attempt to balance the lack of control that she seems to have over the press’s representation of her identity.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.039 | 0.040 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".