MétaCan
Menu
Back to cohort
Record W2600698925 · doi:10.3138/jcfs.46.4.499

Ageing Population and Family Support in Spain

2015· article· en· W2600698925 on OpenAlexvenueno aff
Laura Carrascosa

Bibliographic record

VenueJournal of Comparative Family Studies · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSolidarityContext (archaeology)Affect (linguistics)Population ageingWelfare stateFamily supportDemographic economicsPopulationWelfareSocial supportEconomic growthPsychologySociologyPolitical scienceGeographyEconomicsSocial psychologyDemographyMedicine

Abstract

fetched live from OpenAlex

Historically the family has been an important source of support and solidarity. However in the current Spanish economic context the crisis has strengthened the mechanisms of family solidarity. In particular the households headed by people 65 years and over are reducing the impact of the crisis. But older people are also receiving help. Demographic aging involves profound social changes that affect the structure and composition of families. The reduction in average household size, the increase in single person households and weakening family and personal networks, affect the welfare and quality of life of the older people. In Spain the family continues to be the main source of support and help in old age due to limited development of the welfare state. The aim of this paper is to reflect on the effect that changes in demographic processes and family dynamics will have on support that older people receive from their families in Spain and Europe. Knowledge of family and residential context of people over 65 years becomes essential when addressing efficient policies for integration from the perspective of age. The considerable increase of older people in developed countries, combined with changes in family-related behaviour and weakening family networks, have caused concerns about older people’s family support in future.

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 score0.633
Threshold uncertainty score0.701

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.162
GPT teacher head0.407
Teacher spread0.245 · 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

Citations6
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Comparative Family StudiesSame topicMigration, Aging, and Tourism StudiesFrench-language works237,207