4 - The Role of NGOs in Canada and the USA in the Transformation of the Socio-Cultural Structures in Africa
Bibliographic record
Abstract
This paper aims to explain how International Non-Governmental Organisations (INGOs) in Canada and the United States of America assist in maintaining the West’s hegemonic position in ongoing globalisation process, with specific ref- erence to Africa. The process begins at the local community level with ordinary citizens in North America. These people are exposed to ‘development pornogra- phy’ through a plethora of visual, text and audio input via the mass media and popular culture, which present the African lifeworld as inferior and primitive, and African people as helpless, hapless, and in the throes of an unending series of epidemics on the short road to extinction. African cultures are portrayed as backward, atavistic, stuck in their primeval past, and needing ‘modernisation’ from the West. This African lifeworld is used to describe and portray Africa in ways that justify the importance of civil society organisations (CSOs) – chari- ties, aid workers, business people, missionaries and non-governmental organi- sations (NGOs) – in ‘intervening’ in the African continent’s seemingly inexora- ble human crises. INGOs, in turn, use this image as ‘compassion usury’, tugging on the heartstrings of North Americans to donate generously to various projects in Africa. Large amounts of money, goods and time are donated by ordinary people to help re-make the so-called inferior traditional lifeworlds of Africans in accordance with Western visions. In return, these donors receive generous rewards for their contributions, in the form of tax deductions, community recognition, and development fund awards. Many of these donors are so motivated that they become development tourists who regularly visit Africa, bringing back ‘mercy-soliciting’ images to raise funds and create jobs for NGOs. Horrific pic- tures further reinforce negative stereotypes and misconceptions about Africa. In this way CSOs, particularly those recognised in Canada and the USA as interna- tional NGOs, not only unwittingly export and impose North American values on Africans, but also serve and maintain the global status quo of Western hegemony and African dependence.
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.025 | 0.012 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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.
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".