“My Story, Our Rights”—Navigating the System When Living With Young Onset Dementia in Finland
Bibliographic record
Abstract
This paper discusses the rights of people with young onset dementia in their everyday lives. It does this by collaborating with co-author Petri, who was diagnosed with dementia whilst of working age. Petri shares his story of navigating the system to find resources for living a good and valuable life with dementia, starting with the challenges he faced in getting a diagnosis and accessing services, through to advocating for people living with dementia to defend their rights. The narrative form of Petri’s overall story is progressive; it reveals a range of challenges yet portrays a person living as well as possible with dementia. Key themes in Petri’s story are accompanied by a dialogue of Finnish laws and regulations, as well as literature on dementia. Besides increasing awareness and fostering change, Petri sees opportunities such as advocacy work as a rehabilitative activity for himself and as a way to show that it is possible to live an active life with dementia. From a practical and ethical point of view, it is crucial that academic researchers carefully consider how to remain sensitive to the lived experience of realizing one’s rights and maintain a regular dialogue and transparency during the co-authoring process.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.028 | 0.026 |
| Scholarly communication | 0.014 | 0.015 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.006 | 0.010 |
| 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".