Identity in Old Age. Reconceptualizing Ageing through Alice Munro’s Short Fiction
Bibliographic record
Abstract
In our progressively older society, ageing studies are acquiring more importance as a research domain in the social sciences, and the study of literature is gaining ground in this interdisciplinary field. Short stories are one of the most suitable literary genres to examine the representations of old age, because they throw light on the subtleties of human psychology from different perspectives. Through a close reading of four short stories by Alice Munro, this dissertation studies how the famous Canadian writer has portrayed old age in her short fiction, and to what extent the process of ageing affects the identity of her older characters. In addition to these two research questions, and by taking into account short stories written in different periods, the study also tries to observe whether the portrayal of ageing has changed throughout Munro's career. The analysis of the short stories selected will prove that retirement, internment in residential homes and dementia directly affect the identity of the older protagonists. Still, as will be shown, these characters do not completely lose their sense of personhood and learn to adapt to their new lifestyle. It can be concluded that Alice Munro depicts the process of ageing through a multifaceted approach, portraying both its deficiencies and strengths.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.014 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".