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Record W2602576308 · doi:10.1177/1471301217699676

Responding to Aggression and Reactive Behaviours in the Home

2017· article· en· W2602576308 on OpenAlexaffabout
Rachel Herron, Mark W. Rosenberg

Bibliographic record

VenueDementia · 2017
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsQueen's UniversityBrandon University
FundersWorld Health Organization
KeywordsAggressionPsychologyDementiaDevelopmental psychologyMedicineDisease

Abstract

fetched live from OpenAlex

Behaviours such as hitting, spitting, swearing and kicking can be a common response to personal, social and environmental challenges experienced by people with dementia. Little attention, however, has been given to how partners in care experience and respond to these behaviours in the home. This paper examines the emerging theme of 'aggression,' in seven interviews with nine former partners in care of people with dementia in Ontario, Canada. We explore how partners in care talk about, interpret and respond to these behaviours drawing on recent conceptualizations of structural and interpersonal violence in health and social geography and contributing to the growing body of research on relational care. We discuss the responses to, and implications of, these behaviours at a range of spatial scales and identify important considerations for future research.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.222
Threshold uncertainty score0.441

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.009
Scholarly communication0.0020.001
Open science0.0010.004
Research integrity0.0010.001
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 head0.073
GPT teacher head0.465
Teacher spread0.393 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations12
Published2017
Admission routes2
Has abstractyes

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