Bibliographic record
Abstract
Founded over a century ago, the Mennonite Central Committee (MCC) is regarded as one of the most important institutional carriers of Canadian and American Mennonite identity. Generations of Mennonites and others have served with the organization, carrying out development, disaster relief, and peacebuilding work in over fifty countries globally. The Service of Faith offers an ethnography of MCC’s Christian development work in Indonesia, exploring the challenges, conundrums, theologies, and ethical commitments that shape Mennonite service. The success of religious-based development work depends on effectively bridging very different cultural and religious worlds. Braiding together extensive ethnographic and archival research, Philip Fountain analyzes MCC’s practices of cultural translation in the Indonesian context. While the particularities of Mennonite religious values are deeply influential for MCC’s work, in practice its humanitarian project involves collaboration with a range of actors who come from widely varied religious positions. In taking a nuanced, case-specific approach to understanding how faith shapes moral projects, Fountain challenges mainstream claims to secular neutrality and the tendency to dismiss or disapprove of religious motivations in development work. Exploring the diverse ways in which Mennonite convictions permeate MCC’s work in Indonesia, The Service of Faith confronts the question of whether religion has a legitimate place in international development work.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".