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Record W2971279127 · doi:10.5296/ijhrs.v9i3.15191

Required Leadership Traits for an Organizational Success

2019· article· en· W2971279127 on OpenAlexaboutno aff
Neeraj Kumari, Devi Singh

Bibliographic record

VenueInternational Journal of Human Resource Studies · 2019
Typearticle
Languageen
FieldDecision Sciences
TopicLeadership, Behavior, and Decision-Making Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTransformational leadershipLeadership stylePsychologyJob satisfactionPerceptionQuarter (Canadian coin)Public relationsSocial psychologyPolitical scienceGeography

Abstract

fetched live from OpenAlex

‘Managerial Leadership’ takes an Organization to greater heights, towards the achievement of vision and mission of the Organization. The study aims to assess the perception of the employees about leadership effectiveness in relation to the employee’s satisfaction at BHEL. The study also identifies areas of strengths and need for the improvements in different aspects of leadership which may help in improving the satisfaction level of the employees and hence, better performance at the work place. The LSQ (Leadership Survey Questionnaire) has been used to identify Leadership styles in the organization. The LSQ was sent to the different executives at both the sites and at the Head quarter. The study was conducted at the executive level (E1-E8) at 35 sites. The study concluded that a statistical significant relationship exists between transformational leadership and some factors of employee satisfaction. It found that a statistically significant relationship exists between leadership style and employee satisfaction levels in BHEL.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.002

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 head0.373
GPT teacher head0.482
Teacher spread0.109 · 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 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

Citations2
Published2019
Admission routes1
Has abstractyes

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