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Record W1983569895 · doi:10.2307/4127279

Fields of the Lord: Animism, Christian Minorities, and State Development in Indonesia.

2002· article· en· W1983569895 on OpenAlexaffvenue
Joshua Barker

Bibliographic record

VenuePacific Affairs · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Studies and History
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAnimismState (computer science)Political scienceSociologyAnthropologyComputer science

Abstract

fetched live from OpenAlex

Religious and ethnic violence between Indonesia's Muslim majority and Christian minorities escalated dramatically after Suharto resigned in 1998. In this ethnographic study of Christianization in Indonesia, Lorraine Aragon delineates some of the background to this conflict. The work departs from many studies of comparative religion by positing that religions - like cultural groups - no longer can be considered as isolated or inherently orthodox entities. Moreover, the realization of particular religions in their social contexts are best understood through an examination of institutions that mediate between the power of governments and the agency of particular individuals. To this end, Aragon closely details Central Sulawesi highlanders' institutions of farming and community leadership, regional patterns of exchange, ancestral cosmology, shamanic healing, sacrificial rituals, and ritual speech and song to determine the subtle shifts that have caused contemporary forms of these events to be deemed either Christian or unchristian.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.217
Teacher spread0.200 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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

Citations75
Published2002
Admission routes2
Has abstractyes

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