Diaspora, Trauma, and Unconsciousness: A Deep Dive Into Souvankham Thammavongsa’s How to Pronounce Knife
Bibliographic record
Abstract
This research highlights the psychological experience of the characters in the collection of short stories How to Pronounce Knife (2020), by Souvankham Thammavongsa. Souvankham Thammavongsa is a contemporary writer from Canada. She was born in a Lao refugee camp. She won notable awards like the Giller Prize for her works which include How to Pronounce Knife, a collection of short stories. This book talks about several experiences of the Diaspora people. This paper examines, by using Freud’s Psychoanalytical theory, the characters in the collection of short stories How to Pronounce Knife. It is crucial to identify and examine specific instances from the short story collection that illustrate the psychoanalytical theory, which explores the intricacies of human desires and dreams, their inherent presence in human nature. The characters in this short story collection have certain features that showcase their personalities as diasporic people. By using some of the major themes of Diaspora, this paper explores the psychological pain and suffering of the diaspora characters in this short story collection How to Pronounce Knife.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.023 | 0.029 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 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".