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Record W2940982211 · doi:10.3928/00989134-20190328-02

Aging Individuals With Down Syndrome and Dementia as Teachers: Learnings from Staffin a Developmental Disability Program in Long-Term Care

2019· article· en· W2940982211 on OpenAlexaboutno aff
Annette Lane, Marlette B. Reed, Pamela Hawranik

Bibliographic record

VenueJournal of Gerontological Nursing · 2019
Typearticle
Languageen
FieldMedicine
TopicDown syndrome and intellectual disability research
Canadian institutionsnot available
Fundersnot available
KeywordsDementiaPsychologyLong-term careGerontologyTerm (time)Gerontological nursingDevelopmental psychologyMedicinePsychiatryNursing

Abstract

fetched live from OpenAlex

Older adults with Down syndrome (DS) and dementia are an emerging sub-population. With much longer life spans than decades ago, issues have arisen as to where these aging adults will live and how nurses and other staff in facilities can provide effective care to these individuals. The current article presents a research study that examined the learnings of nurses and staff members working within a western Canadian program for older adults with DS and dementia. These learnings include: the importance of learning from each other; importance of collaboration; how individuals with developmental disabilities communicate; older adults with DS and dementia differ from older adults with dementia; and residents' impact on staff. [Journal of Gerontological Nursing, 45(5), 17-22.].

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)0.005
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.121
Threshold uncertainty score0.241

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0080.003
Scholarly communication0.0040.003
Open science0.0020.006
Research integrity0.0010.002
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 head0.027
GPT teacher head0.344
Teacher spread0.317 · 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

Citations3
Published2019
Admission routes1
Has abstractyes

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