‘The problem with Leonard’: A critical constructionist view of need-driven dementia-compromised behaviours
Bibliographic record
Abstract
This critical constructionist case study of ‘Leonard,’ a man with frontotemporal dementia living on a special care unit predominantly populated by people with Alzheimer’s disease and related dementias, explores how healthy others’ perceptions of the prevailing physical and psychosocial environment were influenced by Leonard’s behaviour which, in turn, was influenced by people’s perceptions of him as a ‘problem’. Data were obtained through participant observations, individual interviews with staff and residents, and focus groups with family members and nursing staff. Leonard’s ‘needs-driven dementia-compromised’ behaviours are not recognized as such by many of the healthy others with whom he co-creates his psychosocial environment; rather he is constructed as deviant, which undermines his selfhood as well as his quality of life. Education of staff and family members as well as broad organizational change is needed to address the issues underlying the problems for which Leonard is blamed but instead arise largely from the environment within which Leonard is situated.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 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) | 0.001 | 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".