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Record W4401955410 · doi:10.1515/9780228022497

The Service of Faith

2024· book· en· W4401955410 on OpenAlexaboutno aff
Philip Fountain

Bibliographic record

VenueMcGill-Queen's University Press eBooks · 2024
Typebook
Languageen
FieldSocial Sciences
TopicReligion, Society, and Development
Canadian institutionsnot available
Fundersnot available
KeywordsFaithService (business)SociologyPolitical scienceBusinessPhilosophyTheologyMarketing

Abstract

fetched live from OpenAlex

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.616
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.016
GPT teacher head0.235
Teacher spread0.219 · 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; a candidate call from one teacher head, not a consensus.

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

Citations1
Published2024
Admission routes1
Has abstractyes

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