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Record W1983014817 · doi:10.1093/jts/fln106

Rendering the Word in Theological Hermeneutics: Mapping Divine and Human Agency. By MARK ALAN BOWALD.

2009· article· en· W1983014817 on OpenAlexaboutno aff
Anthony C. Thiselton

Bibliographic record

VenueThe Journal of Theological Studies · 2009
Typearticle
Languageen
FieldArts and Humanities
TopicBiblical Studies and Interpretation
Canadian institutionsnot available
Fundersnot available
KeywordsEnlightenmentHermeneuticsPhilosophyAgency (philosophy)FaithEpistemologyMoral agencyReading (process)TheologyLinguistics

Abstract

fetched live from OpenAlex

Mark Bowald, of Redeemer University College, Canada, traces the absence of references to the divine agency of the Bible to the Enlightenment and to Kant. The purpose of the book, he states, is ‘to challenge a misleading legacy of Enlightenment epistemology’ (p. 19). This legacy, he claims, produced ‘confused’ readings of Scripture, which failed to take account of divine agency in the inspiration of Scripture. He argues that hermeneutics since the Enlightenment marginalizes divine agency. It concentrates on the reader and the act of reading. Bowald blames especially Kant's epistemology, which turns, he argues, on the distinction between opinion, belief, and knowledge. Notions about God, according to Kant, can never be more than beliefs, in that they proceed from a subjective awareness rooted in the world and one's moral nature, but do not proceed from an ‘objective’ demonstration. Kant, Bowald argues, suffers from two limitations among others. First, potential knowledge of God can never be ‘true’ or ‘pure’ knowledge; second, we cannot rise above ‘faith’ as the medium of knowledge of God. This excludes our taking account of others’ knowledge of God, or their prior judgements.

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)0.004
metaresearch head score (Gemma)0.008
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 score0.029
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.007
Science and technology studies0.0060.029
Scholarly communication0.0100.015
Open science0.0010.004
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0060.002

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 head0.073
GPT teacher head0.290
Teacher spread0.217 · 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
Published2009
Admission routes1
Has abstractyes

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