UNICEF IWASH Project, Northern Region, Ghana : an adapted training manual for groundwater development
Bibliographic record
Abstract
This report is an adapted training manual, with specific best practice recommendations for \ngroundwater development practitioners working in the Northern Region, Ghana. It is designed to \nbe used in conjunction with the existing comprehensive training manual ‘Developing \nGroundwater: a guide to rural water supply’ by MacDonald, Davies, Calow and Chilton (2005). \nThe additional guidelines provided in this supplementary report are specific to the Northern \nRegion of Ghana, and have been informed by a review of groundwater development in the \nregion which BGS carried out on behalf of UNICEF in 2010-2011. \nThe Northern Region is a difficult area in which to find and develop groundwater resources. For \nthis reason, more resources – time and money – need to be focussed on careful borehole siting \nand development in order to maximise success. This includes detailed desk and field \nreconnaissance surveys; the effective use and interpretation of geophysical siting methods; \ncollection of good quality data during drilling and test pumping; rigorous recording and \nmanagement of data; and effective interpretation, sharing and use of hydrogeological \ninformation by all groundwater development practitioners. This report, and the associated \nmanual ‘Developing Groundwater’, provide practical help for carrying out these activities \neffectively. \nThe authors gratefully acknowledge those persons who contributed to the formation of these \nguidelines, who include: \n UNICEF Ghana – Othniel Habila, Kabuka Banda and David Ede \n Community Water and Sanitation Agency (CWSA), Ghana – John Aduakye \n Canadian International Development Agency (CIDA) – Hydrogeological Assessment \nProject (HAP) – James Racicot \n All participants at the UNICEF/BGS workshop and training programme held in Tamale, \nNorthern Region, from 7 to 18 February 2011.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.141 | 0.054 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".