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What God Would Have Known

2024· book· en· W4395005286 on OpenAlexaff
J. L. Schellenberg

Bibliographic record

Venuenot available
Typebook
Languageen
FieldArts and Humanities
TopicTheology and Philosophy of Evil
Canadian institutionsMount Saint Vincent UniversityDalhousie University
Fundersnot available
KeywordsPhilosophyPsychologyComputer science

Abstract

fetched live from OpenAlex

Abstract This book links facts about human intellectual and moral development to what any God who existed at the time of Jesus would have known, and on the basis of that connection it crafts twenty new arguments for the conclusion that classical Christian doctrine is false. These arguments represent what the author calls ‘the problem of contrary development’. Human origins in deep time, human religion, the formation of the New Testament, human psychology, violence, sex and gender—advances in our understanding on all these fronts are brought into interaction with the doctrines of sin, spiritual helplessness, salvation, the divinity of Jesus, the Holy Spirit, and revelation, with the result that the latter are shown to be vulnerable to refutation in new ways. For example, it is argued that given what any God would have known at the time, it must be false that God was incarnate in Jesus of Nazareth, who acquiesced in a religious narrative that centrally featured an oversimplified understanding of human psychology, an inappropriate response to wrongdoing, and the condoning of violence. The book concludes by developing, in connection with its results, two Christian versions of the problem of divine hiddenness and an argument against the existence of God from the historical success (but salvific failure) of Christianity. By taking account of all these things, it is maintained, philosophers can bring a better balance to work on Christianity in philosophy, negotiating a shift from Christian philosophy to the philosophy of Christianity.

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)0.001
metaresearch head score (Gemma)0.004
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: Other · Consensus signal: Other
Teacher disagreement score0.023
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0040.008
Scholarly communication0.0050.007
Open science0.0010.003
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0230.006

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 head0.047
GPT teacher head0.245
Teacher spread0.198 · 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
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

Citations2
Published2024
Admission routes1
Has abstractyes

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