Longitudinal detection of dementia through lexical and syntactic changes in writing: a case study of three British novelists
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We present a large-scale longitudinal study of lexical and syntactic changes in language in Alzheimer's disease using complete, fully parsed texts and a large number of measures, using as our subjects the British novelists Iris Murdoch (who died with Alzheimer's), Agatha Christie (who was suspected of it), and P.D. James (who has aged healthily). We avoid the limitations and deficiencies of Garrard et al.'s [(2005), The effects of very early Alzheimer's disease on the characteristics of writing by a renowned author. Brain, 128 (2): 250–60] earlier study of Iris Murdoch. Our results support the hypothesis that signs of dementia can be found in diachronic analyses of patients' writings, and in addition lead to new understanding of the work of the individual authors whom we studied. In particular, we show that it is probable that Agatha Christie indeed suffered from the onset of Alzheimer's while writing her last novels, and that Iris Murdoch exhibited a 'trough' of relatively impoverished vocabulary and syntax in her writing in her late 40s and 50s that presaged her later dementia.
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.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it