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Record W1460756039 · doi:10.1177/0020852315576706

Leadership competencies for a global public service

2015· article· en· W1460756039 on OpenAlexaff
Tim A. Mau

Bibliographic record

VenueInternational Review of Administrative Sciences · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Policy and Administration Research
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsOptimal distinctiveness theoryPublic sectorPublic relationsPublic servicePolitical scienceLeadership studiesLeadershipLeadership stylePsychology

Abstract

fetched live from OpenAlex

The notion of a global public service has been put forth in the literature as a means of addressing a number of policy issues that can no longer be addressed by a nation-state in isolation. This article sets out to address whether it is possible to formulate and implement a leadership competency model that could be used to select, develop and reward these global public servants and, if so, what leadership competencies they would require. Evidence will be drawn from both the literature on the competencies required for global managers/leaders as well as various public sector leadership competency models. It is argued that more thought needs to be given to how a leadership competency framework might be fruitfully employed to buttress such a cadre of individuals. Points for practitioners Public services around the world have been embracing the use of leadership competency models as part of their human resources management frameworks for the past few decades. This research examines a number of the various models that have been employed with the intent of identifying key competencies that would be more universal in nature. Additional research needs to be conducted to ensure that such models reflect the distinctiveness of the public sector.

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)0.004
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.982
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.634
GPT teacher head0.550
Teacher spread0.084 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations35
Published2015
Admission routes1
Has abstractyes

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