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A Study on Millennial Generation in Vietnam on the Factors to Motivate Employees

2020· article· en· W3045958909 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Analysis and Applications · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicGenerational Differences and Trends
Canadian institutionsnot available
Fundersnot available
KeywordsVietnameseWork (physics)Field (mathematics)Test (biology)Job designPoint (geometry)Organizational culturePublic relationsPsychologySociologyKnowledge managementPolitical scienceJob performanceSocial psychologyComputer scienceJob satisfactionMathematicsEngineering

Abstract

fetched live from OpenAlex

In this paper, we will overview the most of theories in the field of motivation and retest the practical contexts in reality to tackle the questions of the ways to motivate employees. The test of this paper is expected to find out the factors which could upgrade the motivation index of employees in work environment. The model of contexts that influence the work motivation in special case of Vietnamese youngsters will perform and organize into 4 components: Organizational and team culture/ climate, Leadership/ Social relations, Organizational practice and policies and Work role and job demand/ design in the third chapter. Last but not least, the final sector would figure out the gap in this research in point out the direction for future research performances in the field of motivating employees.

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.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.193
Threshold uncertainty score0.168

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.077
GPT teacher head0.357
Teacher spread0.280 · 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