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Record W2003813280 · doi:10.2166/wst.2010.513

A methodology to bridge the water information gap

2010· article· en· W2003813280 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueWater Science & Technology · 2010
Typearticle
Languageen
FieldDecision Sciences
TopicComplex Systems and Decision Making
Canadian institutionsMinistry of Transportation of Ontario
FundersRijkswaterstaatVirginia Agricultural Experiment Station, Virginia Polytechnic Institute and State University
KeywordsBridge (graph theory)StructuringProcess (computing)Information needsComputer scienceInformation gapInformation systemInformation managementProcess managementEngineeringKnowledge managementBusiness

Abstract

fetched live from OpenAlex

The metaphor of the water information gap is used to describe the discontent between information users and information producers about the use of and need for specific information. This paper describes the rugby-ball methodology for specification of information needs that was developed on the basis of an analysis of the water information gap and insights from the literature on policy- and decision-analysis, problem-structuring, and information management. The methodology consists of a process-architecture to manage the process of assessing information needs and a structure to organise the information needs related to water policy objectives. The methodology was developed and enhanced through a Reflection-in-Action process in which interaction between ideas and practice leads to improved results. The paper describes the methodology and its development, and concludes both on the development process and on the abilities of the methodology to narrow the water information gap.

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.

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)0.014
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.588
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0040.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.007

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 head0.220
GPT teacher head0.427
Teacher spread0.207 · 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