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Leadership in Public Sector: A Discussion from Theoretical and Practical Aspects

2013· article· en· W2165164836 on OpenAlexvenueno aff
Zhihong Zeng, Wei Chen, Zeng Xiao-ying

Bibliographic record

VenueCanadian social science · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsPublic relationsLeadershipNeuroleadershipPublic sectorLeadership styleShared leadershipServant leadershipTransactional leadershipQuality (philosophy)Corporate governanceGovernment (linguistics)Leadership studiesWork (physics)Public servicePsychologyPolitical scienceManagementEconomicsEpistemologyLaw

Abstract

fetched live from OpenAlex

Leadership is a critical component of good public governance (OECD, 2001). Effective leadership can bring greater efficiency and quality of service for the organization as well as the increase in personal satisfaction at work. Moreover, it can develop innovation and ability to adapt to the external environment for government. Therefore, there is a great need to improve the quality of leaders. Effective leadership is determined by both heredity and environment. This paper goes on to prove leadership in public sector can be learned from theoretical and practical aspects. As for the theoretical aspects, some innate traits, such as personality can only explain 30% of the leadership effectiveness, and even some personal traits, such as problem solving skill, expertise can be learned. Environment plays the most important role in the leadership of public sector. Emergence and leadership behaviors can contribute to leadership effectiveness. So a lot of leadership development programs, such as formal training, mentoring and feedback can be used to cultivate leadership.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.684
Threshold uncertainty score0.998

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 studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.050
GPT teacher head0.252
Teacher spread0.202 · 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 teacher head, not a consensus.

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

Citations12
Published2013
Admission routes1
Has abstractyes

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