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Record W7128820398 · doi:10.3929/ethz-c-000789892

Disentangling Responsibility: Perspectives on Dementia Prevention From Stakeholders in Canada, Germany and Switzerland

2025· other· en· W7128820398 on OpenAlexaboutno aff
Niklas Petersen, Mattia Andreoletti, Alessandro Blasimme, Cynthia Lazzaroni, Annette Leibing, Silke Schicktanz

Bibliographic record

VenueETH Zürich Research Collection · 2025
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsNormativeDementiaCriticismMoral responsibilityPublic policyHealth carePublic healthPoliticsWelfare

Abstract

fetched live from OpenAlex

Dementia prevention has become a priority in medical research and public health. Various medical, social and environmental risk factors have been identified; however, medical studies, media discourses and health policies predominantly centre on individual-level prevention and promote personal responsibility for maintaining cognitive health. This emphasis on individual preventive efforts faces increasing criticism for being ethically problematic, medically insufficient and reflective of a neoliberal responsibilisation of (cognitive) ageing. Our study, based on 60 semi-structured qualitative interviews with stakeholders involved in dementia research, care and health policy from Canada, Germany and Switzerland, situates the preventive turn within contemporary ageing cultures and welfare policies. By examining the epistemic and normative arguments underlying current debates on dementia prevention, we illustrate how stakeholders justify both personal and governmental responsibilities in preventing dementia. Although managing and mitigating various risk factors throughout life is often framed as a matter of personal responsibility, many stakeholders advocate combining individual-level prevention with population-level efforts to address social inequalities that affect the risk of developing dementia. Drawing on the interview study, we highlight the importance of recognising the political and normative foundations and implications of dementia prevention strategies.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.526
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.095
GPT teacher head0.373
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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