MétaCan
Menu
Back to cohort
Record W2998982928 · doi:10.1177/0265407519899704

Convoys of perceived support from adolescence to midlife

2020· article· en· W2998982928 on OpenAlexafffund
Shichen Fang, Matthew D. Johnson, Nancy L. Galambos, Harvey Krahn

Bibliographic record

VenueJournal of Social and Personal Relationships · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsUniversity of Alberta
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsSocial supportPsychologyFamily supportDepression (economics)Developmental psychologyYoung adultClinical psychologySocial psychologyMedicine

Abstract

fetched live from OpenAlex

Data from 963 Canadians at ages 18 (late adolescence), 25 (young adulthood), and 43 (midlife) were used to explore convoys of perceived social support from parents, other family, friends, partners, coworkers, and children. Latent profile and latent transition analyses revealed two support profiles at each age, distinguished by amount of family support. Those with high family support had a high likelihood (approximately 80%) of remaining in that profile from one life stage to the next, while those with low family support had an equal likelihood (approximately 50%) of remaining there or transitioning into high support. Those with high family support at all three ages had fewer symptoms of depression in midlife than those with low family support at all ages. These findings highlight the prominence of family of origin in social convoys of perceived support and implications of perceived support for midlife mental health.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.807
Threshold uncertainty score0.389

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.134
GPT teacher head0.354
Teacher spread0.221 · 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 source (direct Gemma or distilled Codex), 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

Citations18
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Social and Personal RelationshipsSame topicHealth disparities and outcomesFrench-language works237,207