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Record W4240224133 · doi:10.17771/pucrio.acad.27547

A INFLUÊNCIA DA CONFIANÇA ORGANIZACIONAL NOS ÍNDICES DE ROTATIVIDADE E ABSENTEÍSMO DO SETOR DE TRANSPORTE: UMA ANÁLISE COMPARATIVA DE CASOS

2016· dissertation· pt· W4240224133 on OpenAlexaff
DANIEL SOUSA DO AMARAL

Bibliographic record

Venuenot available
Typedissertation
Languagept
FieldDecision Sciences
TopicBusiness and Management Studies
Canadian institutionsCascades (Canada)
Fundersnot available
KeywordsAbsenteeismDismissalBusiness administrationBusinessSoundnessTurnoverPsychologyManagementSocial psychologyPolitical scienceEconomics

Abstract

fetched live from OpenAlex

The studies on trust have proliferated in the national and international literature. However, the relationship between organizational trust, absenteeism and turnover is rarely discussed in the literature. In order to fill this gap, this dissertation aims to analyze the impact of organizational trust on the turnover and absenteeism levels, based on two premises: (1) organizational trust impact on turnover rate; (2) the higher the organizational trust, the lower the absenteeism rate. Therefore based on a qualitative methodology was carried out a comparative case study between two bus companies, located on greater Rio de Janeiro, with the questionnaires Trust Scale Employee of the Organization (ECEO) prepared by This study concluded that: (1) the greater the confidence in promoting employee growth and the organizational soundness, the lower will be the turnover levels; (2) the results demonstrate a negative association between rules relating to the dismissal of employees and turnover levels; (3) it is not possible to assume the influence of organizational trust in absenteeism companies.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.298
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0180.001

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 head0.366
Teacher spread0.308 · 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; both teacher heads agree on what is shown here.

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
Published2016
Admission routes1
Has abstractyes

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