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Record W4412737969 · doi:10.3138/jcfs.55.2.04

Examining Older Adults’ Filial Expectation and Evaluation of Adult Children

2024· article· en· W4412737969 on OpenAlexvenueno aff
Yubo Hou

Bibliographic record

VenueJournal of Comparative Family Studies · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicIntergenerational Family Dynamics and Caregiving
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyDevelopmental psychologyGerontologySocial psychologyMedicine

Abstract

fetched live from OpenAlex

This study explored the relationship between filial discrepancy and older adults’ overall filial piety rating of their adult children. Along with the prevailing context of individualism, more discrepancies have emerged between what older adults expect and what they actually receive, and this may have a complex influence on intergenerational harmony. In total, 245 older adults (average age 64.6 years, range 55 to 93) provided 422 questionnaires (177 provided two sets of data, one each for their son and daughter). The results showed that, in general, Chinese older adults expected more from and evaluated their sons and daughters-in-law higher in filial piety than their daughters and sons-in-law. On the specific filial piety factor, sons and daughters-in-law were evaluated as less filial, and daughters and sons-in-law as more filial if they had more sons. The more filial behavior received, the higher the older adults rated their children, especially in terms of attitudinal and mannerly filial behaviors, which supported the discrepancy evaluations hypothesis. The gender of adult children and grandchildren is crucial to older adults’ filial evaluation, and this study reemphasized the importance of filial piety discrepancies rather than filial receipt.

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)0.005
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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.085
GPT teacher head0.398
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 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

Citations0
Published2024
Admission routes1
Has abstractyes

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