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Record W2899582805 · doi:10.1093/geroni/igy023.3126

OLD AND LONELY: THE LONELINESS NARRATIVE, MORAL REGULATION AND THE MEDIA

2018· article· en· W2899582805 on OpenAlexaff
Mary Pat Sullivan, Christina Victor

Bibliographic record

VenueInnovation in Aging · 2018
Typearticle
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsNipissing University
Fundersnot available
KeywordsLonelinessSocial mediaPerspective (graphical)NarrativePopulationPsychologyNonprobability samplingQualitative researchIntervention (counseling)Population ageingGerontologySocial psychologySociologyMedicinePolitical scienceSocial sciencePsychiatryDemography

Abstract

fetched live from OpenAlex

Media campaigns in the United Kingdom portray loneliness as a major social and public health issue. The aim of this study was to explore loneliness representations in the media in England and their possible relationship with key policy initiatives for an ageing population. Using a purposive sampling technique, we adopted a qualitative content analysis of print and digital media targeted at loneliness and older people over a 10 year period. Our findings suggest that skilled marketing within the media has depicted loneliness as an expected consequence of older age, a high burden of ‘disease’ for the health care sector and easily amenable to social intervention. This highly stigmatizing discourse also continues to reinforce the burden of an ageing population. We conclude that there is a need for a critical analysis of loneliness from the perspective of social and cultural constructions of ageing and the positioning of older people in society.

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)0.002
metaresearch head score (Gemma)0.000
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 score0.691
Threshold uncertainty score0.287

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.067
GPT teacher head0.381
Teacher spread0.313 · 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 designObservational
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

Citations1
Published2018
Admission routes1
Has abstractyes

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