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Record W2274878663 · doi:10.2166/wst.2003.0354

Stakeholder involvement in water management: necessity or luxury?

2003· article· en· W2274878663 on OpenAlexaff
Kim Morrison

Bibliographic record

VenueWater Science & Technology · 2003
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicRegulation and Compliance Studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsStakeholderBusinessWater Framework DirectiveEnvironmental planningEnvironmental resource managementAgricultureStakeholder analysisStakeholder managementPublic relationsPolitical scienceEconomicsWater qualityEnvironmental scienceGeography

Abstract

fetched live from OpenAlex

Stakeholder involvement in water management is widely recognized as an important component of the design and implementation of sustainable water management initiatives. Despite this, there remains a deep-rooted resistance to the widespread implementation of programs to prioritize such involvement (as witnessed by, for example, the low priority given to the public involvement element of the European Union Water Framework Directive). This paper addresses the issue of stakeholder involvement by first confronting the fact that it is not a water issue, per se. Such diverse fields as economics, agriculture, public health, pollution prevention, business and education have also identified stakeholder involvement as a difficult but necessary component of successful action in their fields. For the water sector, the issue of stakeholder involvement as either a necessity for sustainable water management, or a luxury to be used to complement traditional approaches, is discussed.

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)0.042
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.042
Threshold uncertainty score0.224

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0420.041
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0040.026
Scholarly communication0.0090.019
Open science0.0010.007
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.0040.000

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 head0.044
GPT teacher head0.242
Teacher spread0.197 · 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 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

Citations28
Published2003
Admission routes1
Has abstractyes

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