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Record W2770092296 · doi:10.1080/10376178.2017.1411203

‘We don’t even have Wi-Fi’: a descriptive study exploring current use and availability of communication technologies in residential aged care

2017· article· en· W2770092296 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueContemporary Nurse · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsnot available
FundersAlzheimer Society
KeywordsAged careTelephone surveyDescriptive statisticsLong-term careNursingMedicinePsychologyBusinessMarketing

Abstract

fetched live from OpenAlex

BACKGROUND: There has been significant growth in communication technologies. However, it is unknown to what extent RACFs accommodate such technologies. AIM: To explore the use and availability of communication technologies for use by residents within RACFs in Queensland, Australia. METHODS: A descriptive, structured telephone survey. Every 10th alphabetically listed facility from a total sample of n = 462 were telephoned and staff were invited to complete the survey. RESULTS: Forty-one out of a total of 93 RACFs completed the survey. The telephone was by far the primary form of communication used by residents to communicate with family and friends (n = 40; 97.6%). Conversely, the use of web-connection communication software (Skype or similar) was uncommon. CONCLUSION: The use and availability of communication technologies is limited within RACFs, highlighting a significant lag in the uptake within the sector.

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.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.318
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.155
GPT teacher head0.354
Teacher spread0.199 · 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