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Stress in Relation to Work Ethic

2022· book-chapter· en· W4281827779 on OpenAlexaff
S. Jack Olszewski

Bibliographic record

VenueAdvances in human resources management and organizational development book series · 2022
Typebook-chapter
Languageen
FieldDecision Sciences
TopicEthics in Business and Education
Canadian institutionsYorkville University
Fundersnot available
KeywordsHumanityOccupational stressWork (physics)Engineering ethicsCoping (psychology)Environmental ethicsValue (mathematics)Relation (database)PsychologySociologySocial psychologyPolitical scienceEngineeringLawComputer scienceClinical psychology

Abstract

fetched live from OpenAlex

Stress is a common disease of the 21st century that affects people under various conditions. One of the main sources of stress in everyone's life is their job, and work stress has become a common and costly problem in work environments. Ethics is a branch of philosophy that has been explored and discussed since the birth of humanity. It has gained important relevance and value in our modern world as we continue to examine the importance of social responsibility and develop global standards of human ethics. The issue of occupational stress is one of the most important issues in modern science and focuses on the sources of occupational stress and their impact on work efficiency and the quality of organizational decisions. Often, these decisions are guided by our understanding of ethics. In this chapter, the author explores the relationship between stress, work ethic, and the stress coping strategies employed by working people.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.050
GPT teacher head0.312
Teacher spread0.262 · 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 designTheoretical or conceptual
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

Citations4
Published2022
Admission routes1
Has abstractyes

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