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Record W2313273210 · doi:10.1177/0020715214561132

Eating and ageing: A comparison over time of Italy, Ireland, the United Kingdom and France

2014· article· en· W2313273210 on OpenAlexvenueno aff
Amy Erbe Healy

Bibliographic record

VenueInternational Journal of Comparative Sociology · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMultinomial logistic regressionKingdomGeographyDescriptive statisticsNorthern irelandFood habitsDemographySocioeconomicsEnvironmental healthMedicineSociologyEthnology

Abstract

fetched live from OpenAlex

This research analysed household budget survey data from Ireland, the United Kingdom, France and Italy from 1985/1987 to 2004/2005 to determine how age groups differ in terms of food-related practices, how these patterns are changing and to see if these patterns differ across countries. Descriptive analysis and fractional multinomial logistic regression were used. Food practices seem to be changing over time across all age cohorts in Ireland and the United Kingdom; older people have different food practices now than they would have had a few decades ago. However, in Italy and France, food-related practices seem to be related to age and life course with older people eating out less as they age than they did when they were younger. If these trends continue, older people will continue to prepare their own meals to a greater extent in Italy and France in the future with the retention of home preparation skills, while the home preparation of food will continue to decline in Ireland and the United Kingdom. These trends have implications for the health and well-being of older people in those countries.

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)0.001
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 score0.494
Threshold uncertainty score0.340

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.041
GPT teacher head0.371
Teacher spread0.330 · 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

Citations10
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Comparative SociologySame topicMigration, Aging, and Tourism StudiesFrench-language works237,207