Bibliographic record
Abstract
This essay explores the various ways of talking about senility and how the two competing (or, possibly, complementing) discourses—the biomedical dementia discourse and the discourse of senility as part of “normal” aging—affect our perception of and attitudes toward old age. Moreover, I explore the role of fiction in articulating senility. As my approach combines critical gerontology with narratological analysis, it belongs to the burgeoning domain of literary gerontology, a discipline that embraces various literary genres from fiction to nonfiction. This double perspective of literary studies and cultural gerontology makes it possible to examine senility as a historically and culturally specific concept and phenomenon. My aim is to demonstrate with two examples from contemporary Russian short prose (Nina Katerli’s story “Na dva golosa” [In Two Voices] and Nina Sadur’s story “Stul” [The Chair]) how a literary work can be related to prevailing cultural, sociological, and medical discourses on and norms of aging. With tools of narratology I shed light on the literary devices deployed in the stories to articulate the experience of senility from the viewpoint of the elderly protagonists themselves. Text in English DOI: 10.25285/2078-1938-2020-12-2-169-186
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".