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The Impact of Zhongyong Thinking on Employee’s Mental Health

2024· article· en· W4392373749 on OpenAlexaff
Xinlu Li

Bibliographic record

VenueLecture Notes in Education Psychology and Public Media · 2024
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCompromiseMental healthPsychologyMeaning (existential)ModerationSocial psychologySociologyPsychotherapistSocial science

Abstract

fetched live from OpenAlex

Zhongyong is a moral standard set forth by Confucian culture, meaning maintaining neutrality and moderation. Many people tend to have a misunderstanding of Zhongyong thinking, believing that Zhongyong represents compromise and the middle position. They might consider that such thinking is detrimental to healthy mental development. However, Zhongyong thinking is not the same as compromise, and instead it allows the coexistence of contradictions and opposites. After reviewing a series of previous articles on Zhongyong thinking and mental health, it is shown that Zhongyong thinking plays a moderating role in the employees’ psychological state. Moreover, the factors affecting the influence of Zhongyong thinking on employees' mental health include psychological resilience and psychological security. Ultimately, the review found that one of the main reasons for the moderation of psychological states in the workplace is because it affects emotional regulation and alleviates symptoms of depression and anxiety. Plus, Zhongyong thinking related training also was shown some benefits. A limitation of previous studies is that subjective questionnaires were used to measure the level of Zhongyong thinking and other psychological variables, which could be less accurate. Future research directions could explore how to accurately demonstrate dynamic Zhongyong thinking processes through experimental and longitudinal design.

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)0.000
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 score0.813
Threshold uncertainty score0.713

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.059
GPT teacher head0.445
Teacher spread0.386 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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