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Record W4399117890 · doi:10.5337/2024.215

Country water quality profiles: towards developing an African Water Quality Program (AWaQ)

2024· report· en· W4399117890 on OpenAlexaff
P. Mukuyu, N. Jayathilake, Moshood N. Tijani, Josiane Nikiema, Chris Dickens, J. Mateo-Sagasta, Deborah V. Chapman, Stuart Warner

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsUniversité du Québec
Fundersnot available
KeywordsQuality (philosophy)Water qualityBusinessEnvironmental scienceWater resource managementGeographyBiologyEcologyPhysics

Abstract

fetched live from OpenAlex

The African Ministers’ Council on Water (AMCOW) Secretariat committed to design and implement an African Water Quality Program (AWaQ) in its Strategic Operational Plan (2020-2024) considering the guiding frameworks it uses such as the Africa Water Vision 2025, United Nations Sustainable Development Goals (SDGs), and the African Union Agenda 2063: The Africa We Want. AMCOW reached out to the International Water Management Institute (IWMI) to support the development of such a program. AWaQ builds on the rich experiences and lessons learned from past and ongoing regional and subregional water quality initiatives across Africa by different players, including African Union institutions, and the wider members of the World Water Quality Alliance (WWQA), as well as the AMCOW African Water and Sanitation Sector Monitoring and Reporting System (WASSMO). The five phases of developing an African Water Quality Program (AWaQ) are explained in the following papers: 1. State of Water Quality Monitoring and Pollution Control in Africa (phase 1-2) 2. Innovations in Water Quality Monitoring and Management in Africa (phase 3-4) 3. A Framework for an African Water Quality Program (AWaQ) (phase 5) 4. Country Water Quality Profiles This report is the last in the above list and contains the results of an AMCOW-IWMI Africa-wide survey that was conducted to gain a better understanding of the water quality situation of several countries in the region. The survey was conducted across Africa through the AMCOW network of African country representatives. Of the 54 AMCOW Member States, 31 responded to the survey offering their inputs on different water quality-related aspects. Water quality profiles of 17 of those countries are presented in this paper. Each country profile contains a statistical summary of the water quality situation, a summary of the water pollution sources and impacts, the policies and institutions governing water quality, and some of the most important water monitoring and pollution control initiatives. Although there are variations across countries in terms of the status of available capacity for water quality monitoring and management as well as pollution control, water pollution remains a critical challenge that provides an impetus for AWaQ.

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)0.008
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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.710
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0180.004

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 head0.128
GPT teacher head0.418
Teacher spread0.290 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations1
Published2024
Admission routes1
Has abstractyes

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