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IWRM: Ideology or Methodology?

2023· reference-entry· en· W4318461561 on OpenAlexaff
Larry A. Swatuk, Adnan Ibne Abdul Qader

Bibliographic record

VenueOxford Research Encyclopedia of Environmental Science · 2023
Typereference-entry
Languageen
FieldEngineering
TopicWater resources management and optimization
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsIntegrated water resources managementPolitical sciencePanacea (medicine)IdeologyStakeholderSet (abstract data type)MainstreamingPublic relationsPoliticsManagement sciencePublic administrationBusinessWater resourcesEconomicsLawComputer science

Abstract

fetched live from OpenAlex

Abstract Integrated water resources management (IWRM) was introduced as a conceptual solution to solve complicated problems of water management; however, since its inception, practitioners remain divided on its utility. Critics argue that it lacks practicable and working examples and that ongoing support is tantamount to little more than an ideological position. Supporters counsel patience and point to a variety of positive—if partial—outcomes, while aiming to address some of the most meaningful criticisms involving the devolution of decision-making authority, stakeholder participation, and gender mainstreaming. While the notion of “integrated management” resonates positively across the water world, critics and supporters alike are quick to note that in application it will play out differently depending on physical, sociocultural, economic, and political factors. Put differently, while the idea has universal appeal, the means and methods of achieving IWRM will vary. Comparative analysis reveals some common characteristics of performance well known across the development industry. In particular, direct engagement of resource users from project and program conception through to implementation, monitoring, and evaluation increases the likelihood of long-term positive outcomes. In contrast, top-down, elite-driven actions are likely to be resisted. Far from a panacea, IWRM is most usefully regarded as a “sensibility,” offering practitioners a set of signposts to guide actions and loose parameters within which to set policy.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.791
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.097
GPT teacher head0.335
Teacher spread0.237 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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