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Record W2100770781 · doi:10.1080/08039410.2015.1036112

Building Resilient Organizations for Effective Service Delivery in Developing Countries: The Experience of Ghana Water Company Limited

2015· article· en· W2100770781 on OpenAlexaff
Joshua Jebuntie Zaato, Frank L. K. Ohemeng

Bibliographic record

VenueForum for Development Studies · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural risk and resilience
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsDeveloping countryBureaucracyService delivery frameworkBusinessPublic sectorDemocracyPublic relationsWater sectorService (business)Public administrationEconomic growthPolitical scienceMarketingEconomicsEngineeringWater supplyPolitics

Abstract

fetched live from OpenAlex

Public organizations in developing countries can only be effective if they are able to develop and implement public policies effectively and efficiently. However, what continues to bother scholars is how to ensure that such bureaucratic organizations are also accountable and democratic. Some have argued that the solution lies with the building of merit-based organizations. Nevertheless, we believe that a critical factor in building efficient organizations in developing countries is the designing and building of resilient organizations. In this article, we provide a theoretical framework for building resilient organizations in developing countries and use it to examine water sector reforms in Ghana.

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)0.005
metaresearch head score (Gemma)0.006
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0100.005
Scholarly communication0.0030.004
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.035
GPT teacher head0.275
Teacher spread0.240 · 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

Citations3
Published2015
Admission routes1
Has abstractyes

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