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Record W2062375401 · doi:10.1177/0095399713498747

The Administrative Sherpa and the Journey of Public Service Leadership

2013· article· en· W2062375401 on OpenAlexaff
Catherine Althaus

Bibliographic record

VenueAdministration & Society · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Policy and Administration Research
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsMetaphorScrutinyPublic servicePublic administrationService (business)Administration (probate law)Public relationsSociologyTransactional leadershipPolitical scienceLawBusiness

Abstract

fetched live from OpenAlex

The sherpa is offered as a helpful metaphor amid the rich and diverse metaphorical landscape describing public administration at the interface between senior public servants and ministers. The sherpa model acknowledges the complexity and nuanced leadership now demanded in the Westminster tradition, offering fresh tools for practitioners to think more critically about their role and how they can improve leadership skills. It also offers theoretical ability to incorporate relevant but underdeveloped factors, such as the environment, into the administrative leadership equation, thus enlarging issues at stake and forces demanding scrutiny, if administrative leadership is to be better understood.

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)0.006
metaresearch head score (Gemma)0.007
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: none
Teacher disagreement score0.015
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.029
Scholarly communication0.0150.007
Open science0.0010.007
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0070.001

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 head0.261
GPT teacher head0.406
Teacher spread0.145 · 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

Citations8
Published2013
Admission routes1
Has abstractyes

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