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Record W1987913665 · doi:10.1002/hfm.20518

Municipal service delivery: A multi‐stakeholder framework

2012· article· en· W1987913665 on OpenAlexaff
Paul R. Messinger

Bibliographic record

VenueHuman Factors and Ergonomics in Manufacturing & Service Industries · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicService and Product Innovation
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsService delivery frameworkSocial mediaStakeholderProcess (computing)Service (business)Stakeholder engagementBusinessProcess managementFace (sociological concept)Service designService modelKnowledge managementPublic relationsComputer scienceMarketingWorld Wide WebPolitical scienceSociology

Abstract

fetched live from OpenAlex

Abstract A large number of services that affect people's lives in modern economies are delivered by cities. This paper proposes a framework for municipal service delivery. Within this framework, the paper highlights challenges cities face when combining human and automated service delivery. The paper also describes how to harness social media to facilitate citizen engagement in the process of addressing some of these challenges. Lastly, the paper underlines the need for institutional arrangements and flexible software systems that can facilitate citizen‐centered municipal service delivery and social media engagement. © 2012 Wiley Periodicals, Inc.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.001
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 head0.109
GPT teacher head0.265
Teacher spread0.157 · 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

Citations7
Published2012
Admission routes1
Has abstractyes

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