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Record W2142917384 · doi:10.1017/hor.2015.53

Theology, Science, and Technology: Framing an Encounter in Light of Lonergan and Ricœur

2015· article· en· W2142917384 on OpenAlexaff
James R. Pambrun

Bibliographic record

VenueHorizons · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Ecology, and Ethics
Canadian institutionsSaint Paul University
Fundersnot available
KeywordsFraming (construction)ElaborationEpistemologySociologyMode (computer interface)PhilosophyComputer scienceHistoryHumanitiesArchaeology

Abstract

fetched live from OpenAlex

This article proposes a theological approach to the encounter between theology and the world of science and technology. A suitable locus for encounter is the different partners' shared commitment to the desire to understand. I draw on the work of both Bernard Lonergan and Paul Ricœur to describe understanding as the enactment of a pattern of cognitional operations. However, the theoretical mode of understanding proper to science is distinct from the practical mode of understanding proper to technology. Lonergan's elaboration of the “intellectual” pattern of operations is drawn on to enhance an encounter with science, while Ricœur's elaboration of the “action” pattern is drawn on to enhance an encounter with technology.

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)0.011
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 score0.015
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0140.072
Scholarly communication0.0150.017
Open science0.0020.009
Research integrity0.0070.010
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 head0.024
GPT teacher head0.321
Teacher spread0.297 · 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
Published2015
Admission routes1
Has abstractyes

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