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Record W4283766146 · doi:10.3390/rel13070608

To Tend or to Subdue? Technology, Artificial Intelligence, and the Catholic Ecotheological Tradition

2022· article· en· W4283766146 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueReligions · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicTheology and Philosophy of Evil
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsTechnocracyManagementIBMExecutive directorLawPolitical scienceSociologyEnvironmental ethicsPhilosophyPolitics

Abstract

fetched live from OpenAlex

In February 2020, the president of Microsoft, the executive vice president of IBM, the director general of the Food and Agriculture Organization (FAO) of the United Nations, and the former Italian Minister of Innovation joined the president of the Vatican’s Pontifical Academy for Life in Rome to sign The Rome Call for AI Ethics. In doing so, they promoted a shared sense of responsibility and commitment—by industry, government, and Church—to uphold certain ethical standards in the areas of digital innovation, artificial intelligence, and technological progress. In this article, I discuss The Rome Call for AI Ethics in conjunction with Pope Francis’ rendering of integral ecology and the technocratic paradigm in Laudato Si’. My aim here is to link Catholic teaching on technology (using AI as a starting point) to the environment and the ecological crisis.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.386
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.071
GPT teacher head0.264
Teacher spread0.193 · 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