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Record W4384694726 · doi:10.22215/etd/2023-15541

The Design of Long-Term Care Homes: Dignity and Safety in Continence Care

2023· dissertation· en· W4384694726 on OpenAlexaffabout
Sara Abdou

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsCarleton University
Fundersnot available
KeywordsDignityThematic analysisLong-term careNursingTerm (time)MedicineQualitative researchPsychologySociologyPolitical science

Abstract

fetched live from OpenAlex

This study explored the impact of long-term care home design on dignified and safe continence care practices.The research begins with information on continence care work, the people involved, and the design of long-term care homes through a literature review.Through this, I identified scant information on the relationship between the architecture/ interior design of long-term care homes and continence care practices.As a result of this scant academic attention to the 'design', I conducted primary research through semi-structured interviews and consultation design sessions with stakeholders from a long-term care home in Ontario, Canada.I developed a theoretical framework using 3 theories to explore the study's research questions and data.A thematic analysis revealed the underlying values and emotions intertwined with continence care processes that are a reflection of long-term care design.The generated design concepts and recommendations for the home case study were inspired by the thematic analysis.

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)0.009
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.011
Scholarly communication0.0070.003
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.017
GPT teacher head0.276
Teacher spread0.260 · 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 designQualitative
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

Citations2
Published2023
Admission routes2
Has abstractyes

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