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Record W7012744504

The big question

2005· other· en· W7012744504 on OpenAlexaboutno aff

Bibliographic record

VenueCGSPace A Repository of Agricultural Research Outputs (Consultative Group for International Agricultural Research) · 2005
Typeother
Languageen
FieldMedicine
TopicAssisted Reproductive Technology and Twin Pregnancy
Canadian institutionsnot available
Fundersnot available
KeywordsPovertyQuarter (Canadian coin)EnthusiasmGlobeRidiculousNatural resource
DOInot available

Abstract

fetched live from OpenAlex

Professor Ajaga Nji spent more than 25 years travelling to some of the most under-privileged corners of the world to ask the question that has been puzzling him ever since he was a young man in Cameroon: why do poor people remain poor?\nHis travels took him to most parts of his native Africa, as well Why Poor People Remain Poor: Key Elements for Poverty Alleviation and Sustainable Developmentas to Asia, Europe and the United States of America. Wherever he went, he spoke to poor people, and painstakingly recorded his conversations and interviews as he went.\nOver the years, a pattern began to emerge. Whether he was talking to farmers in Machacos, Kenya, or to herders in Sabongari, in the North West Province of Cameroon, a common thread of injustice, poor access to natural resources and lack of opportunities and education ran through the picture. Given that it took the author quarter of a century to investigate this vast subject, it would be absurd to try to synthesise the answers here.\nIn one chapter, he comes up with 26 reasons why poor people remain just that. One clue, however, comes with the account of a poor fisherman he met in Cameroon, distraught because his old canoe leaked badly and because his net only caught a few young fish. This book is written for the fisherman, who might come to understand[ ]that he is poor because the rich, deep-sea fishermen use their wealth, greater resources and larger vessels to catch the big fish, pushing only the fries to the shores into his net, writes the author, many years after that encounter.\nBut this is not a book of despair. The author is Professor of Rural Sociology and Technology Issues at the University of Dschang, Cameroon and has long experience of practical ways of alleviating poverty, many of which he outlines in his book.\nHe concludes with the conviction that while poverty can probably never be eliminated altogether, it can be reduced in good measure through focused, targeted, anti-poverty programs based on a commitment to justice, peace, good governance, democracy and sustainable development. \n\nWhy Poor People Remain Poor: Key Elements for Poverty Alleviation and Sustainable Development\nBy A Nji\nDeScholar Press\n2004. 240 pp.\nISBN 9956 401 05 6\nUS$20 15\nAjaga Nji & Associates\nPO Box 138\nDschang\nCameroon\nFax: + 237 345 19 55\nEmail: ajaga_nji@yahoo.com

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)0.003
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.136
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.003
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 head0.050
GPT teacher head0.366
Teacher spread0.316 · 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
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
Published2005
Admission routes1
Has abstractyes

Explore more

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