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Record W3092416318 · doi:10.35632/ajis.v28i4.1229

Earth Empire and Sacred Text

2011· article· en· W3092416318 on OpenAlexaboutno aff
Mahan H. Mirza

Bibliographic record

VenueAmerican Journal of Islam and Society · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Society, and Development
Canadian institutionsnot available
Fundersnot available
KeywordsDivinityEmpireOrder (exchange)Quarter (Canadian coin)PhilosophyTheologyReligious studiesSociologyLawPolitical scienceHistoryArchaeology

Abstract

fetched live from OpenAlex

There is a new trend in the progressive quarter of American EvangelicalChristianity to form common bonds with Muslims. From this impulsestem books such as Miroslav Volf’s Allah: A Christian Responseand Carl Medearis’ Muslims, Christians, and Jesus: Gaining Understandingand Building Relationships, as well as organizations such as RickLove’s Peace Catalyst and Yale Divinity School’s Reconciliation Program.David Johnston’s robust Earth, Empire and Sacred Text falls withinthis trend (although these are by no means monolithic attempts and each must be evaluated on its own terms). As an Evangelical Christianwith an academic streak and extensive international experience, Johnstonis uniquely positioned to not only reach out to Muslims but alsoto educate his fellow American Christians. The book is an extraordinaryundertaking and may be considered a three-volume work collapsedinto one. Devout yet pragmatic, Johnston is prepared to engagethe reality of the world in order develop a theology that acknowledgesits own limitations. Johnston combines intellectual rigor with politicalactivism, while remaining theologically inclusive yet authentic ...

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.007
Scholarly communication0.0060.003
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0130.002

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.

Opus teacher head0.019
GPT teacher head0.271
Teacher spread0.252 · 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 designTheoretical or conceptual
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

Citations0
Published2011
Admission routes1
Has abstractyes

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