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Record W2963257323 · doi:10.5430/ijfr.v10n4p90

Reasons Are Given for the Current Wildcat Strikes in Vietnam: The Blue-Collar Workers' Perspective

2019· article· en· W2963257323 on OpenAlexvenueno aff
Hung Van Tran

Bibliographic record

VenueInternational Journal of Financial Research · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsnot available
Fundersnot available
KeywordsVietnameseSeniorityCollarAllowance (engineering)Perspective (graphical)Demographic economicsSocioeconomicsPolitical scienceBlue collarGeographySociologyBusinessLawEconomicsOperations managementFinance

Abstract

fetched live from OpenAlex

Despite the vast research by researchers on Vietnam's wildcat strike, little is known of the perspective of the Southern Focal Economic Zone. The overall reason that emerges from the literature included: (1) raising wages for workers; (2) contributing to social security for workers; (3) and paying a seniority allowance. The aim of the present research is to figure out the reasons for the current wildcat strikes among Vietnamese blue-collar workers. A group of 936 Vietnamese blue-collar workers (387 males and 549 females) from four Southern Vietnam cities participated in the survey. They completed the Reasons are given for Wildcat Strikes questionnaire. The descriptive results showed that the highest mean among those reasons is ‘‘Labor regulations at the company are too strict’’. The result of this research emphasizes the impact of each reason by investigating nonoffice workers’ perspective so as to predict which the potential reasons are for future strikes in Southern Vietnam.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.055
GPT teacher head0.431
Teacher spread0.376 · 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 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

Citations6
Published2019
Admission routes1
Has abstractyes

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