Sharing Knowledge for Community Development and Transformation: a Handbook
Bibliographic record
Abstract
Oxfam Canada is a non-profit, international development organization that works with community groups to help people attain better health and nutrition, more secure incomes and a stronger say in their future as well as responding in emergency situations. Oxfam Canada works in over 20 countries in Central and South America, the Caribbean, and Africa. In Canada, Oxfam educates people on issues of global poverty and advocates for positive changes in policies that directly affect the worlds poor (www.oxfam.ca). Oxfam Canada is one of the 12 Oxfam organizations around the world that form Oxfam International. The Horn of Africa Capacity Building Programme (HOACBP) is a bilateral programme entirely funded by the Canadian International Development Agency (CIDA) and managed by Oxfam Canada and Oxfam Québec, from 1997 to 2002. HOACBP supports groups and organizations that are grounded at the local level, engaged in non-formal education, information and communications, gender equality and justice. It promotes the principles of equity and participatory development through-out the Horn of Africa and supports organizations that espouse and reinforce these principles. Copyright permission to translate and/or reproduce this text in whole or in part is granted by Oxfam Canada, as long as the text is kept in its integrity and the author, Kingo J. Mchombu, and the publisher, Oxfam Canada, are acknowledged. Second edition published in 2004 by Oxfam Canada.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.015 | 0.016 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 0.008 |
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".