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Record W3093615802 · doi:10.3138/jcfs.51.3-4.009

Burdens, Resilience, and Mutual Support: A Comparative Study of Families in China and South Korea Amid the COVID-19 Pandemic

2020· article· en· W3093615802 on OpenAlexvenueno aff
Bin Lian, Soo‐Yeon Yoon

Bibliographic record

VenueJournal of Comparative Family Studies · 2020
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsDisadvantagedUnemploymentRecessionPsychological resilienceEconomic growthChinaFamily resiliencePandemicSociologyDevelopment economicsCoronavirus disease 2019 (COVID-19)Political sciencePsychologyEconomicsSocial psychologyMedicine

Abstract

fetched live from OpenAlex

As the ongoing COVID-19 pandemic disrupts established daily routines, it underlines the role that families play in redefining social order and reorganizing people’s economic and social lives. In this paper, we investigate methods that Chinese and South Korean families have adopted to cope with the rapid changes brought on by the COVID-19 pandemic. We emphasize families’ responses to sudden changes in three domains: education and home schooling, economic downturn and unemployment, and mental health challenges. By integrating online education and remote working into a new form of family life and sharing economic and emotional risks among members, families shape social order during a period of unprecedented uncertainty. We highlight the fact that family members experience intensified work-family or school-family conflicts. Disadvantaged families are the most severely affected, as they are at high risk of job loss and lack proper protections. The absence of institutional protections and interventions has created further economic and emotional hardships for these vulnerable families. Informal and nonregular workers require more stable labor market conditions for the well-being of their families. Future research may include a systematic data collection and analysis of disadvantaged families, as this would offer a better understanding of the challenges and untenable choices that families face during times of crisis.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score0.712

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.282
GPT teacher head0.481
Teacher spread0.199 · 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 designQualitative
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

Citations17
Published2020
Admission routes1
Has abstractyes

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