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Record W1995563167 · doi:10.1353/cja.2006.0006

The Degree of Bedroom Personalization in Institutional and Homelike Settings for Persons with Dementia: A Quantitative Investigation

2005· article· en· W1995563167 on OpenAlexaff
Anderson Chuck, Doris L. Milke, Charles H.M. Beck

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2005
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBedroomPersonalizationQuality (philosophy)PsychologyDegree (music)Measure (data warehouse)Empirical researchComputer scienceBusinessMarketingStatisticsGeographyMathematicsDatabase

Abstract

fetched live from OpenAlex

ABSTRACT The purpose of this study was to provide an empirical measure of bedroom personalization and a descriptive characterization of the types of items included in a personalized space. The study compared the extent of personalization in three types of bedrooms, varying as to their homelike quality (private-homelike, private-institutional, and ward-institutional). A measure of the relative degree of personalization was obtained by recording the number of personal items for each room and dividing the number of items per room by each room's available vertical and horizontal surface area. The degree of personalization was found to be significantly greater in private-homelike rooms than in private-institutional or ward-institutional rooms. This study provides the first demonstration that personalization of a resident's bedroom can be quantified and opens the way for studies of factors contributing to the effect (e.g., facility regulations, family, and staff attitudes) and empirical studies of presumed consequences (e.g., resident satisfaction and improved functioning).

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)0.004
metaresearch head score (Gemma)0.012
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.000
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 head0.023
GPT teacher head0.257
Teacher spread0.233 · 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

Citations9
Published2005
Admission routes1
Has abstractyes

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Same venueCanadian Journal on Aging / La Revue canadienne du vieillissementSame topicDementia and Cognitive Impairment ResearchFrench-language works237,207