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Record W604754814 · doi:10.4324/9781315622309

Marketing Management and Communications in the Public Sector

2017· book· en· W604754814 on OpenAlexaff
Martial Pasquier, Jean‐Patrick Villeneuve

Bibliographic record

Venuenot available
Typebook
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsÉcole Nationale d'Administration Publique
Fundersnot available
KeywordsBusinessPublic sectorMarketing communicationMarketing managementMarketingPolitical science

Abstract

fetched live from OpenAlex

This updated edition of Marketing Management and Communications in the Public Sector provides a thorough overview of the major concepts in public sector marketing and communications, two fields that have continued to grow in importance for modern public administrations. With extended coverage of topics such as social marketing and institutional communication, the authors skilfully build on the solid foundations laid down in the previous edition. Replete with real-world case studies and examples, including new material from the USA, Australia, and Asia, this book gives students a truly international outlook. Additional features include exercises and discussion questions in each chapter and an illustrative extended case study. This refreshed text is essential reading for postgraduate students on public management degrees, and aspiring or current public managers. The Open Access version of this book, available at https://www.taylorfrancis.com/books/e/9781315622309, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 license.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.056
Threshold uncertainty score0.189

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0020.001
Scholarly communication0.0060.005
Open science0.0000.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0560.025

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 head0.079
GPT teacher head0.287
Teacher spread0.208 · 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 designNot applicable
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

Citations21
Published2017
Admission routes1
Has abstractyes

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