Faith in Development: Donald K. Faris’s Path to a New Mission in the Postcolonial Era
Bibliographic record
Abstract
After the Second World War, Western nations, multilateral agencies, and non-governmental organizations (NGOs) began providing development assistance to newly emerging nations in Asia and Africa.Their engagement reflected the great need for humanitarian assistance in those nations and the pragmatic stimulus of the Cold War.The pace, at first halting, accelerated dramatically in the 1960s, which the UN proclaimed the United Nations Development Decade. 1 Far from perceiving this trend as a threat to their historic roles and their influence in the non-western world, many mainstream missionaries embraced it, either by serving with secular development agencies or by encouraging the mission organizations of their churches to make multi-faceted assistance to the developing world a priority.In the course of the 1960s, the mission organizations of many mainstream churches did in fact make this transition, in effect becoming faith-based NGOs.For historians of western Christianity as well as for development studies specialists, much can be learned, I believe, by investigating intersections between secular and faith-based approaches to international assistance in the postcolonial era.For the past several years I have been researching a secular NGO, CUSO, originally called Canadian University Service Overseas.Established in 1961, the same year as the US Peace Corps, CUSO was the first
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".