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Record W3126446694 · doi:10.5430/jnep.v11n6p9

The digital development within society that persons of 75 years and older in European countries have been part of: A scoping review protocol

2021· review· en· W3126446694 on OpenAlexvenueno aff
Moonika Raja, Jorunn Bjerkan, Ingjerd Gåre Kymre, Kathleen Galvin, Lisbeth Uhrenfeldt

Bibliographic record

VenueJournal of Nursing Education and Practice · 2021
Typereview
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsnot available
FundersNord universitet
KeywordsProtocol (science)DemographicsOlder peopleGrey literatureOrder (exchange)Process (computing)Health carePublic relationsPolitical scienceBusinessMedicineEconomic growthGerontologyComputer scienceMEDLINESociologyAlternative medicineEconomics

Abstract

fetched live from OpenAlex

Over the past decades countries of the world have experienced increase in the share of older people in demographics and the number is expected to rise even more. People are becoming more than ever dependent on digital technologies. The aim of this study is to map the body of literature concerning historical digital development over the last 20 years that people of 75 years and older in European countries have been part of. Moreover the goal is to identify research gaps in the existing literature in order to inform future research. The five-staged Arksey and O’Malley methodology framework is used to guide the scoping review process. Research strategy and eligibility criteria are defined. The study selection is made based on the eligibility criteria. A framework developed for the scoping review informs the charting of data from the included studies. Results will be summarized with criteria relevant for policy-makers, healthcare providers and the public.

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 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)0.003
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.942
Threshold uncertainty score0.593

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.127
GPT teacher head0.478
Teacher spread0.350 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

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
Published2021
Admission routes1
Has abstractyes

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