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Record W2969299092 · doi:10.1186/s41039-019-0104-5

Empowering older adults’ informal, self-directed learning: harnessing the potential of online personal learning networks

2019· article· en· W2969299092 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueResearch and Practice in Technology Enhanced Learning · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsUniversity of Saskatchewan
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsInformal learningLifelong learningThe InternetLeverage (statistics)FacilitationAdaptation (eye)Social mediaPsychologyKnowledge managementComputer scienceInternet privacyWorld Wide WebPedagogyArtificial intelligence

Abstract

fetched live from OpenAlex

Information and communication technologies have had an enormous impact on how we live, work, communicate, re-create, and connect with others. However, there is a paucity of research regarding older adult learners’ adoption and adaptation of Internet-based tools, techniques, and resources to support their informal, self-directed lifelong learning goals. This research contributes to our understanding of how and why older adults leverage the Internet and social media tools to create, develop, and maintain online personal learning networks (oPLNs) for the purposes of self-directed knowledge acquisition, personal development, and the facilitation of healthy aging.

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)0.005
metaresearch head score (Gemma)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.706
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.008
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 head0.015
GPT teacher head0.360
Teacher spread0.346 · 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