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Making the Best of It

2008· book· en· W2499435703 on OpenAlexaff
John G. Stackhouse

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicReligion and Society Interactions
Canadian institutionsRegent College
Fundersnot available
KeywordsMoresNothingChristianityReligious studiesTheologyPoliticsSociologyHistoryEnvironmental ethicsPhilosophyLawPolitical scienceEpistemology

Abstract

fetched live from OpenAlex

Abstract What should be the Christian's attitude toward society? When so much of our contemporary culture is at odds with Christian beliefs and mores, it may seem that serious Christians now have only two choices: transform society completely according to Christian values or retreat into the cloister of sectarian fellowship. This book explores the history of the Christian encounter with society, the biblical record, and various theological models of cultural engagement to offer a more balanced and fruitful alternative to these extremes. The book argues that, rather than trying to root up the weeds in the cultural field, or trying to shun them, Christians should practice persistence in gardening God's world and building toward the New Jerusalem. Examining the lives and works of C. S. Lewis, Reinhold Niebuhr, and Dietrich Bonhoeffer for example and direction, it suggests that our mission is to make the most of life in the world in cooperation with God's own mission of redeeming the world he loves. This model takes seriously the pattern of God's activity in the Bible, and in subsequent history, of working through earthly means—through individuals, communities, and institutions that are deeply flawed but nonetheless capable of accomplishing God's purposes. Christians must find a way to live in this world and at the same time do work that honors God and God's plan for us. The model that the book develops discourages the “all or nothing” attitudes that afflict so much of contemporary 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)0.006
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.096
Threshold uncertainty score0.321

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0080.011
Scholarly communication0.0240.020
Open science0.0020.014
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.0960.066

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 head0.115
GPT teacher head0.405
Teacher spread0.289 · 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 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

Citations12
Published2008
Admission routes1
Has abstractyes

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