Bibliographic record
Abstract
There is an increase in cognitive impairment in populations in the developed and developing world as populations age, with over half the cases being caused by Alzheimer’s disease. The number of people with dementia is increasing globally, in line with the ageing profile of the population in each country. In the United Kingdom, it has been established that dementia costs more than cancer, heart disease and stroke put together (Dementia UK 2007). The recent report from the Alzheimer Society of Canada (2009) has reached a similar conclusion, which is that we need to do more. Very many countries are generating their national dementia strategies in response to this challenge. From my work internationally with health and social care workers, I have come to the conclusion that the most significant action we can take is to improve the personal effectiveness of each and every practitioner. Every occupational therapist needs to be thinking carefully of his or her own potential contribution. If the role of the occupational therapist in care for dementia is crucial, this requires a response from universities and colleges to increase the educational elements on dementia in undergraduate and pre-registration programmes. A Scottish survey indicated that there is not much practical input into programmes (Cunningham et al 2006). For example, on one issue alone, occupational therapists need to know much more about dementiafriendly design and technology, so that they can advise people with dementia and their carers on how to maximise their independence at home. Simple measures such as increasing the light levels can make a huge difference, but carers tell me: ‘We were never told … ’ The journey of two people with dementia, even with the same level of underlying pathology, can go in completely different ways. One can maintain independence till right before the end of life, and another can be ushered
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.033 | 0.008 |
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".