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The development of a low-cost sanitation system suitable for Botswana

2022· other· en· W6964715992 on OpenAlexaboutno aff

Bibliographic record

VenueLoughborough University Research Repository (Loughborough University) · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsSanitationGovernment (linguistics)Context (archaeology)Developing countryChristian ministrySettlement (finance)PopulationCapital city

Abstract

fetched live from OpenAlex

Recent studies have revealed that Botswana has probably the highest urban growth rate in Africa and although its four towns are relatively small, their annual population increase in percentage terms is extraordinary. It is estimated, for example, that Gaborone the capital could well grow from its present 33,000 to more than 130,000 by 1985; a fourfold increase within the next decade. The majority of these extra people will be low-income families, all of whom will need homes and the Government is alive to the need to secure their settlement in a planned manner, if we are to avoid a serious squatter situation, in site and service housing areas. The key to successful urban growth in the context of a developing country is a system of domestic sanitation which is inexpensive, efficient in operation, hygienic and socially acceptable and it is for this reason that the Government has authorised a wide-reaching research study.into low-cost sanitation to be carried out by my Ministry in conjunction with the Ministries of Health and Works and Communications and with the assistance of the International Development Research Centre of Canada. I welcome this project and hope that the study and its findings will be of lasting benefit to Botswana and to other countries with similar problems. Foreword by the Hon. L. Makgekgenene Minister of Local Government & Lands Republic of Botswana

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Open science, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.162
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.008
Science and technology studies0.0080.002
Scholarly communication0.0000.001
Open science0.0050.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.042
GPT teacher head0.279
Teacher spread0.236 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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