Bibliographic record
Abstract
From 1843 to 1872, Grace Marks (Sarah Gadon) served time, at the Kingston Penitentiary, for murdering her employer Thomas Kinnear (Paul Gross), and his housekeeper/lover, Nancy Montgomery (Anna Paquin). In 1859, a young American psychiatric doctor, Dr. Simon Jordan (Edward Holcroft), travels to Kingston, under the request of a clemency committee, to study Grace, helping her restore her lost memory of the crimes, with the purpose of writing a favourable report which would concede Grace‟s pardon. This article undertakes the examination of the television miniseries Alias Grace, based on the 1996 homonymous novel by Canadian author Margaret Atwood, by focusing on the analyses of the overall series through a Freudian perspective. It will be argued that each episode is imbued of symbolism that normally escapes the understanding of the viewer. Therefore, I shall illustrate certain aspects connected with Freudian symbolism, according to film studies language, while establishing other important connections to prove the profuse presence of the male gaze and how Grace Marks, an ambivalent protagonist with a fluid personality, navigates this stereotyped 19th society dominated by patriarchal values and invested in the annihilation of the female subject.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.117 | 0.052 |
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".